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Citation: Demertzi, V.; Demertzis, S.;
Demertzis, K. An Overview of Cyber
Threats, Attacks and
Countermeasures on the Primary
Domains of Smart Cities. Appl. Sci.
2023,13, 790. https://doi.org/
10.3390/app13020790
Academic Editors: Stefan Fischer and
Yangquan Chen
Received: 18 October 2022
Revised: 14 December 2022
Accepted: 4 January 2023
Published: 6 January 2023
Copyright: © 2023 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
applied
sciences
Review
An Overview of Cyber Threats, Attacks and Countermeasures
on the Primary Domains of Smart Cities
Vasiliki Demertzi 1, Stavros Demertzis 2and Konstantinos Demertzis 3,4, *
1Computer Science Department, School of Science, International Hellenic University, Kavala Campus,
65404 Kavala, Greece
2School of Spatial Planning and Development, Faculty of Engineering, Aristotle University of Thessaloniki,
54124 Thessaloniki, Greece
3School of Science & Technology, Informatics Studies, Hellenic Open University, 26335 Patra, Greece
4Department of Forestry and Management of the Environment and Natural Resources,
Democritus University of Thrace, 68200 Orestiada, Greece
*Correspondence: kdemertz@fmenr.duth.gr or demertzis.konstantinos@ac.eap.gr
Abstract:
A smart city is where existing facilities and services are enhanced by digital technology
to benefit people and companies. The most critical infrastructures in this city are interconnected.
Increased data exchange across municipal domains aims to manage the essential assets, leading to
more automation in city governance and optimization of the dynamic offered services. However, no
clear guideline or standard exists for modeling these data flows. As a result, operators, municipalities,
policymakers, manufacturers, solution providers, and vendors are forced to accept systems with
limited scalability and varying needs. Nonetheless, it is critical to raise awareness about smart-
city cybersecurity and implement suitable measures to safeguard citizens’ privacy and security
because cyber threats seem to be well-organized, diverse, and sophisticated. This study aims to
present an overview of cyber threats, attacks, and countermeasures on the primary domains of
smart cities (smart government, smart mobility, smart environment, smart living, smart healthcare,
smart economy, and smart people). It aims to present information extracted from the state of the
art so policymakers can perceive the critical situation and simultaneously be a valuable resource
for the scientific community. It also seeks to offer a structural reference model that may guide the
architectural design and implementation of infrastructure upgrades linked to smart city networks.
Keywords:
smart city; cyber threats; cyber attacks; smart government; smart mobility; smart environ-
ment; smart living; smart healthcare; smart economy; smart people
1. Introduction
The smart city [
1
] is an ecosystem that offers various e-government services, ensuring
the seamless access of participating citizens to these services. At the same time, through
an integrated analysis program of the information collected, it promotes the optimal use
of available resources, the improvement of urban space, and its other administrative
services. A city can be considered smart when traditional infrastructure and investment
in human resources support sustainable economic development and high quality of life
based on integrated control technology (
\
). In this spirit, a smart city can connect its
built environment, which is also its natural capital, with society, businesses, and human
resources to develop better services and infrastructure for its perpetual sustainability [2].
As said, the role of ICT is to provide intelligent management tools that will unite
and strengthen the networks of people, infrastructure, companies, and generally available
resources with the aim of sustainable economic development, high quality of life, and
general well-being for the vast majority of citizens. Therefore, a smart city is a city that tries
to face and solve public issues with the help of technology but based on a participatory
process between multiple stakeholders, with the prudent management of natural reseizures
Appl. Sci. 2023,13, 790. https://doi.org/10.3390/app13020790 https://www.mdpi.com/journal/applsci
Appl. Sci. 2023,13, 790 2 of 36
above all, through the participatory action and active participation of citizens, preventing
and many times eliminating social exclusion. Thus, smart cities ensure a networked urban
society which enjoys the benefits of the intelligent management of its affairs with minimal
financial, administrative, and social costs [3].
Here, it is also important to mention that a city cannot be considered smart if useful,
up-to-date, and essential data are not collected, allowing all city entities, from competent
bodies to each citizen, to make smart decisions. Critical data offer convenience, economy,
optimal services, and better and more thoughtful design in a sustainable scheme, where
problems are not simply solved. Still, based on the stored historical data, their hidden
knowledge can reveal trends, allowing relevant agencies to implement preventive policies
to avoid complex situations. As a result, in addition to the direct benefits that any city
entity may receive, these essential data can also provide indirect benefits. For example,
companies can use academic institutions and research bodies in environmental, social,
economic, or transportation studies for appropriate adaptation. Additionally, their products
or services can be used by non-profit and non-governmental organizations to carry out
more effective work [4].
Many urban areas, including energy supply, transportation systems, and telecommu-
nications infrastructure, have started to include parts of a “smart grid”—or a network of
linked sensors inside the city with many advantages. On the other hand, increased connec-
tion brings potentially severe cyber security concerns that have yet to be fully identified
and managed [5].
Based on the above, information security is critical in intelligent cities to ensure higher
confidentiality, availability, and integrity levels. Additionally, it ensures the stability that
national services and organizations require to support sustainable and livable intelligent
environments. Although smart cities are intended to boost productivity and efficiency, they
may pose severe hazards to inhabitants and authorities if cyber security is not prioritized.
For example, the internet of things (IoT) growth reveals new vulnerabilities for in-
truders and other hostile actors to exploit. There are many possible vulnerabilities and
techniques with billions of linked “things” installed in smart cities throughout the globe [
6
].
Summarizing, the following are the most significant security challenges for smart
city environments [7]:
1.
A large and complex attack surface: As cities become more intelligent, they will
incorporate more systems and “systems of systems,” increasing the risk and impact of
an attack and necessitating better control and visibility. Furthermore, the integration
of vendor solutions increases the complexity of intelligent city systems, particularly
during rapid technological transformations.
2.
Inadequate oversight and organization: Complex systems will necessitate more robust
management and governance capabilities. Keeping leadership fully informed of
complex occurrences will require additional resources and capabilities.
In the face of a constantly developing cyber threat scenario, the research community
must supply threat information, prevention, and reaction, as smart cities will give enter-
prizes unparalleled economic potential. However, because of the significant increase in
interconnected devices, cyber threat actors will be presented with an unprecedented attack
surface. Securing smart cities must be a collaborative project involving local administrations
and private sector organizations with an immediate stake in the city’s stable function.
Additionally, ensuring that smart cities are cyber-safe will need identifying and prioritizing
critical assets and behavior-based security—creating a baseline for the routine functioning
of vital support. It should be emphasized that a Smart City’s smartness is measured by
seven aspects in which the city should excel smart government, smart mobility, smart
environment, smart living, smart healthcare, smart economy and smart people [
1
]. These
critical assets must guarantee that all sections of the city conform to minimal benchmarks,
a policy of quick component replacement in case of breach or failure, and a safe segment of
critical private assets from the public network. In this sense, this research aims to identify
Appl. Sci. 2023,13, 790 3 of 36
the cyber threats, attacks, and countermeasures based on the seven primary domains of
smart cities listed above.
The following is the structure of the study: The next section, Section 2, provides an
in-depth description of the primary threat’s attacks and countermeasures that are present
in the seven domains of the smart city networks, how they function, and the associated
effective solutions that have been proposed in the most recent literature. Section 3presents
some concrete recommendations, and Section 4summarizes the primary findings from the
investigation, makes the conclusions and discusses potential avenues for further study.
2. Literature Review
Improving residents’ living standards is the primary goal of constructing smart cities.
From this point of view, a smart city utilizes its resources more effectively and produces an
intelligent ecosystem using the capabilities of digital technology. It requires more inventive
urban transport networks, better water supply and waste-disposal facilities, and more
efficient methods to light and heat buildings in living places. It also involves more creative
ways to deliver democracy and decision participation to citizens. It also means having a
clean and safe environment with accessible public areas and user-friendly financial services
that cater to the population’s requirements without restrictions or exclusions. It should be
emphasized that this connection is achieved with the optimal use of ICT, making smart
citizens of a smart city [2,5].
This study presents an overview of the most dangerous cyber threats, attacks, and
countermeasures to smart city networks based on the seven primary domains of smart
cities [
8
]. In this context, the paper examines indicative but very characteristic cases of cyber
threats related to these categories and the countermeasures proposed in the recent literature.
2.1. Smart Government
Smart governance [
9
] encompasses services that reflect political participation and op-
portunities for citizens’ social inclusion in the administration’s operation. It also encourages
the most efficient administration at the lowest possible cost, in which human and available
resources are fully utilized. Additional training opportunities are also provided, and the
processing of bureaucratic tasks is promoted digitally, removing the citizen from an unfair
waste of time [
10
]. Furthermore, smart governance empowers citizens to participate in pub-
lic decision making and city planning, increasing efficiency and information transparency.
It is necessary to have policy guidelines in place in smart cities to guarantee the
smoothness, security, integrity, and secrecy of smart governance [
11
]. The use of technology
in smart governance must comply with a nation’s laws to be considered legitimate.
The city’s governance services are becoming smarter and more complex [
12
], but
these users must be prepared to confront cyberspace security using more sophisticated
technology and infrastructure [
13
]. Governance service providers are facing growing
problems in adopting a culture of security and information confidentiality as a critical
component of their services [14,15].
2.1.1. Cyber Threats or Attacks
These difficulties will endure as long as regulatory oversight and information security
risks exist. Improving the information security culture inside these firms will most certainly
aid in the safety of governance information, transactions, and personal information and
the continuing performance of essential governance processes [
16
]. For example, risk
identification and mitigation must occur at intersections and in separate domains in the
governance system. The designation from the inter-sector dimension considers the linkages
of the national or municipal sector and the interdependence of the other domestic and
foreign sectors. Furthermore, the intersectoral extent indicates how risk is distributed
throughout interrelated systems (contagion risk) because of parallels in concentration
risk and connectivity. Meanwhile, the inter-time dimension specifies how hazards in the
Appl. Sci. 2023,13, 790 4 of 36
planned system rise over time, primarily risk caused by procedural behavior shifting from
one sector to another [17].
In a smart governance scenario (as depicted in Figure 1), municipal authorities and
local administrations strive to structure and arrange city-wide interventions across various
IoT systems/applications to build an all-in-one and coordinated IoT ecosystem for the full
smart city [
18
]. However, the administration of a whole smart city requires a significant
degree of responsibility for the many tasks to be completed, such as managing IoT systems
(e.g., credential access and control of sensitive data). In addition, technology is necessary
to handle these IoT systems in a coordinated and well-managed manner. The technical
background required to carry out know-how is not recognized by city authorities but by
professionals in the field [14].
Appl. Sci. 2023, 12, x FOR PEER REVIEW 4 of 38
in the governance system. The designation from the inter-sector dimension considers the
linkages of the national or municipal sector and the interdependence of the other domestic
and foreign sectors. Furthermore, the intersectoral extent indicates how risk is distributed
throughout interrelated systems (contagion risk) because of parallels in concentration risk
and connectivity. Meanwhile, the inter-time dimension specifies how hazards in the
planned system rise over time, primarily risk caused by procedural behavior shifting from
one sector to another [17].
In a smart governance scenario (as depicted in Figure 1), municipal authorities and
local administrations strive to structure and arrange city-wide interventions across vari-
ous IoT systems/applications to build an all-in-one and coordinated IoT ecosystem for the
full smart city [18]. However, the administration of a whole smart city requires a signifi-
cant degree of responsibility for the many tasks to be completed, such as managing IoT
systems (e.g., credential access and control of sensitive data). In addition, technology is
necessary to handle these IoT systems in a coordinated and well-managed manner. The
technical background required to carry out know-how is not recognized by city authori-
ties but by professionals in the field [14].
Figure 1. Smart governance scenario.
As a result, municipal governments need ICT-based solutions that offer the elements
necessary for the smart governance of the smart city, emphasizing the following desirable
features [10,11,17]:
1. Permission hierarchy model. Upper-tier authorities need a multilevel governance so-
lution to distribute and transfer authority and duties across various levels of govern-
ment (top-down governance) [19].
Figure 1. Smart governance scenario.
As a result, municipal governments need ICT-based solutions that offer the elements
necessary for the smart governance of the smart city, emphasizing the following desir-
able features [10,11,17]:
1.
Permission hierarchy model. Upper-tier authorities need a multilevel governance
solution to distribute and transfer authority and duties across various levels of gov-
ernment (top-down governance) [19].
2.
Keeping track of duties. Because of the variety of IoT systems and functions supplied
in a smart city, the various authorities must administer a role-based access control
system to allocate and monitor duties.
Appl. Sci. 2023,13, 790 5 of 36
3.
Inclusion. An integrated strategy to accommodate heterogeneity within the same
ICT-based solution is required to facilitate data interchange—third-party API (appli-
cation programming interface) deployment, sharing credentials and permissions, and
so forth.
4.
Support for new systems. A suitable solution that allows the integration of new
IoT systems over time, independent of the technology on which they are based, is
necessary for a dynamic smart municipal, integrating the latest IoT system into the
ICT-based solution offered by the city authorities.
5.
Safety and privacy. It is critical to include security methods in the elements out-
lined above. For example, only authorized and authenticated users may manage
permissions using well-tested and robust processes.
Several ICT-based solutions are needed to address these aspects. For different entities
to cover these features, a common infrastructure that provides ICT-based tools and mech-
anisms is required, ensuring that the same rules and regulations guide IoT systems that
belong to a smart city in terms of smart governance [20].
From this perspective, governance systems must be based on ISO 27001:2013, a global
standard for designing and evaluating an information security management system. This is
important for any governance transaction service provider because transactions as part of a
governance process must be secure and easy to complete. Other references that are often
used for security requirements in technology-based services include the following [21,22]:
1.
COBIT—The Board of Standards Audit and Information Systems Control (ISACA)
publishes the Control of Information and Related Technologies (COBIT), which offers
a control framework for corporate governance and IT governance.
2.
ISO/IEC 15408—These assessment criteria were established and are aligned with the
national security standards.
3.
ITIL (or ISO/IEC 20000 series)—This publication presents a collection of best practices
in IT services management (ITSM), focusing on the IT service process and emphasizing
the user’s important role.
4.
The ISO/IEC 27001—This certificate is often the most basic information technology
standard and determines which other security standards must also comply by a
government organization. For example, if a governance domain offers payment ser-
vices, it must meet, if not exceed, the Payment Card Industry Data Security Standard
(PCI DSS).
2.1.2. Countermeasures
This paper [
4
] shows how proper smart governance and security framework on which
a built adequate security infrastructure could simplify and speed up the certification process
and simultaneously reduce the certification cost.
However, the link between smart governance and data security is quite complex [
23
].
Information security risks and data challenges, such as data transfer, processing, informa-
tion management, network security, and equipment access are significant. The goal is to
improve the smart governance operation environment and big data security by studying
and improving relevant laws and regulations, strengthening access control processing,
improving system protection levels, strengthening the integration of new technologies,
and improving network intrusion detection systems and identity security verification
mechanisms [24].
Only authorized users should be able to access smart governance services, so au-
thentication must be more secure. This research proposes a three-factor authentication
scheme for e-governance applications to address the shortcomings of previous approaches.
Lightweight XOR, one-way, and perceptual hash are used for permission. User identity,
passwords, and biometrics improve scalability and security. The suggested approach
has been verified using the popular Automated Validation of Internet Security Protocols
and Applications tool. According to the security study [
22
], the system is resistant to
numerous threats.
Appl. Sci. 2023,13, 790 6 of 36
In this direction, the authors of this article [
25
] provide a smart data sharing architec-
ture for a smart city environment based on smart contracts and blockchains. The suggested
approach combines data access control and auditing to protect data exchange among stake-
holders. PoT is a complex security solution. The proposed consensus technique uses a
multidimensional trust model to determine smart service provider trustworthiness. The
suggested solution complies with privacy laws and regulations, including GDPR duties.
Additionally, to protect the privacy of this sensitive information, unique software tools
and cryptographic security protocols must be employed using the user’s settings [
16
,
26
].
Hardware devices must be put inside the linked system to improve these security settings.
Because the government is the critical player in delivering electronic services under its
authority, this study has previously presented a citizen-centric multidimensional smart-
card-based e-governance system [
13
]. The authors of [
14
] created a cloud architecture
as an interconnected governance model to handle a large volume of sensitive informa-
tion. The new model’s viability is shown via cloud banking transactions via a linked
governance environment.
On the other hand, there are several practical proposals for this avenue: the authors
of this study [
15
] propose an architecture for the smart governance of heterogeneous IoT
solutions inside smart cities, which includes aspects such as power distribution, security
limitations, and scalability, among others. It is a modified version of the fundamental
architectural paradigm of smart government systems. It relies on digital objects to represent,
store, and interact with physical and digital materials. It also uses open-source technologies
to create the architectural concept and manage digital objects.
Following the proposed transparent and open adjudication procedure, local officials
may assign, for example, the administration of the city’s smart lighting system. This is
done by defining and creating new digital objects as part of the smart city infrastructure for
these new actors: (55555/city/company for the company and 55555/users/manager for the
company manager or representative) and granting permissions to the manager to handle
all smart lighting infrastructure. Similarly, the manager may authorize other members of
the institution, such as the IoT system manager (55555/users/iotmanager), to assign tasks
to trusted employers.
Adopting this multi-level smart governance architecture also addresses one of the
most challenging difficulties in any IoT-based solution: naming (devices or IoT settings).
Because of the handle system and its global infrastructure, each infrastructure installed
following the concept functions as an independent node in a well-structured network
that functions as a domain name system (DNS). In this approach, any IoT material and
smart-governance-related element may be accessible from anywhere, including external
ecosystems, such as other companies, municipal authorities, and smart cities.
Remote e-voting is unquestionably the apex of e-governance in a prosperous smart city.
Remote e-voting is convenient and gives voters simple access. On the other hand, it makes
it simpler for election officials to tally ballots and compile reports. Nonetheless, there has
been increased criticism of the security and integrity of remote e-voting systems. Concerns
have also been expressed concerning the systems’ ability to guard against cyber threats.
A functional remote e-voting system must fulfil a set of regulatory requirements. This
study [
27
] examined the design criteria for remote e-voting systems as mentioned in the
existing literature. The authors investigated whether the current public infrastructure can
support an efficient remote e-voting system that fulfils the design criteria. They discovered
that the present technological infrastructure is insufficient to enable efficient remote e-
voting systems since the technologies that must be installed to meet design criteria are
vulnerable to various cyber assaults.
Decentralized e-voting systems make transparency and dependability difficult to
ensure. Additionally suspicious are the following: protecting the votes’ privacy, secrecy,
and integrity. Blockchain technology has ushered in a new digital age. Blockchain’s
immutability and decentralized design make it ideal for e-voting. It ensures election
authenticity, integrity, transparency, secrecy, and non-repudiation. This article assessed
Appl. Sci. 2023,13, 790 7 of 36
blockchain’s potential for electronic voting. The authors solved all constraints in the current
e-voting system. They created a small-scale e-voting system as a smart contract using
solidity language, which includes hosting the election, certifying voters, and counting votes.
The study [
24
] also demonstrated how zero-knowledge proof might aid in developing safe,
privacy-preserving E-voting systems.
However, implementing blockchain technology in voting systems causes severe delays
in transaction execution. The software solution is only available to a small group of
professionals, which does not inspire trust among voters. This study [
28
] suggests a
novel strategy based on freely accessible verification of all means and procedures that
may generate doubt about the accuracy of the vote count or the secrecy of their results.
Specifically, the authors presented an e-voting system in which an audit of all the hardware
and software of a server that conducts operations linked to potential misuse is performed
to assure confidence. The mechanism guards against illegal influence on votes via bribery
or other forms of pressure. It also monitors all employee operations to control the server’s
functioning from its inception until the election’s conclusion. Simultaneously, the number
of auditors is not restricted, and the verification method is streamlined by using extra
software and hardware. Auditors’ responsibilities include copying and comparing files.
All e-voting system solutions, including audits, are easy to grasp and inexpensive.
2.2. Smart Mobility
Smart mobility aims to make transportation systems “smarter.” Smart transportation
networks, in particular, can better serve the public by improving the safety, speed, and
reliability for local and international accessibility [
29
]. Information and communication
technologies from modern and sustainable transportation systems help consumers plan
their schedules and find the cheapest and fastest routes using transportation-oriented
mobile applications [
30
]. Driver’s passports, license recognition systems, car parking
searching, and prediction are typical applications in smart mobility facilities [31].
A depiction of a smart mobility platform is presented in Figure 2.
Appl. Sci. 2023, 12, x FOR PEER REVIEW 8 of 38
Figure 2. Smart mobility application.
Traffic safety is a significant concern in crowded cities that harms residents [32]. In
this regard, IoT can be more proactive in detecting human errors and reducing traffic ac-
cidents. In the literature, for example, particular research gives valuable insights into al-
lowing smart mobility systems. In [33], an IoT-based system was created by combining
internet platforms and low-cost antenna technologies. The suggested research in [34]
demonstrates the viability of monitoring road safety using developments in IoT. It offers
a low-cost IoT framework for assessing the safety of a road network. In addition, Ref. [35]
presents an overview of the key IoT technologies suggested for smart mobility in smart
city scenarios.
Furthermore, IoT-based solutions must be employed for various applications and
modes of transportation, such as smart traffic, parking, and mobility, to create safer and
cleaner streets. For instance, in [36], an intelligent transportation system was designed to
recognize, locate, track, and monitor buses through exchanging information and commu-
nication. This system is based on the IoT, radio frequency identification (RFID), general
packet radio services (GPRSs), geographic information system (GIS), and global position-
ing system (GPS), among other technologies. Another project that is mentioned in [37]
aims to construct a prototype for intelligent transportation that makes use of a GPS, near
field communication (NFC), and temperature and humidity sensors to monitor automo-
biles and commuter information and the atmosphere inside buses. The [38] research sug-
gests a real-time traffic-monitoring system to solve the issues associated with traffic man-
agement and monitoring. The study used the information gathered from real-time traffic
monitoring to determine roadway problems. In addition, Ref. [39] creates an intelligent
transportation system application that uses internet-of-things platforms, Intel Edison, and
Figure 2. Smart mobility application.
Appl. Sci. 2023,13, 790 8 of 36
Traffic safety is a significant concern in crowded cities that harms residents [
32
]. In this
regard, IoT can be more proactive in detecting human errors and reducing traffic accidents.
In the literature, for example, particular research gives valuable insights into allowing
smart mobility systems. In [
33
], an IoT-based system was created by combining internet
platforms and low-cost antenna technologies. The suggested research in [
34
] demonstrates
the viability of monitoring road safety using developments in IoT. It offers a low-cost IoT
framework for assessing the safety of a road network. In addition, Ref. [
35
] presents an
overview of the key IoT technologies suggested for smart mobility in smart city scenarios.
Furthermore, IoT-based solutions must be employed for various applications and
modes of transportation, such as smart traffic, parking, and mobility, to create safer and
cleaner streets. For instance, in [
36
], an intelligent transportation system was designed to
recognize, locate, track, and monitor buses through exchanging information and commu-
nication. This system is based on the IoT, radio frequency identification (RFID), general
packet radio services (GPRSs), geographic information system (GIS), and global positioning
system (GPS), among other technologies. Another project that is mentioned in [
37
] aims
to construct a prototype for intelligent transportation that makes use of a GPS, near field
communication (NFC), and temperature and humidity sensors to monitor automobiles
and commuter information and the atmosphere inside buses. The [
38
] research suggests a
real-time traffic-monitoring system to solve the issues associated with traffic management
and monitoring. The study used the information gathered from real-time traffic monitoring
to determine roadway problems. In addition, Ref. [
39
] creates an intelligent transportation
system application that uses internet-of-things platforms, Intel Edison, and Raspberry Pi. It
has been proposed that information on traffic conditions may be distributed via standard
instant messaging services, such as WhatsApp.
2.2.1. Cyber Threats or Attacks
As the above research indicates, selecting IoT technology is critical for creating smart
mobility systems [
40
,
41
]. However, the security provided by IoT devices is not guaranteed.
The devices have the propensity to have little computing power, and their hardware
restrictions prevent them from having built-in security mechanisms. This makes the
devices susceptible to vulnerabilities [
42
–
44
]. The IoT devices in a smart city’s ecosystem
control critical transportation infrastructures, so they need strict secure guarantees. In
this point of view, a “Cybersecurity via Determinism” paradigm for the next-generation
“Industrial and Tactile Deterministic IoT” is presented in this study [
45
]. Specifically, in
layer 3, there is a new addition of a forwarding sub-layer called deterministic packet
switches (D-switches), which are straightforward and safe. This sub-layer supports many
deterministic software-defined wide area networks (SD-WANs) in addition to three new
tools that may be used to improve online safety: access control, rate control, and isolation
control. A software-defined networking (SDN) control plane will set up each D-switch with
several deterministic schedules to support D-flows. The control plane of a SDN can insert
millions of deterministic virtual private networks (Dvpns) into layer 3. This paradigm has
a number of advantages, including the following:
1.
All congestion, interference, and distributed denial-of-service (DDOS) assaults
are eliminated.
2. The size of the buffers in D-switches is cut in half.
3. Delays in end-to-end IoT communications are brought down significantly.
4. The D-switches do not require gigabytes of memory to store large IP routing tables.
5. Hardware support is provided in layer 3 for the US NIST Zero Trust Architecture.
6.
Packets within a DVPN can be entirely encrypted using quantum-safe encryption, which
is resistant to attacks by quantum computers using existing quantum algorithms.
7.
The likelihood of an undiscovered cyberattack against a DVPN may be arbitrarily tiny
using lengthy quantum-safe encryption keys.
8.
Savings can approach thousands of dollars annually via decreased capital, energy,
and operating expenses.
Appl. Sci. 2023,13, 790 9 of 36
Because of this, the attack surface is substantially smaller, meaning there are fewer
packets to assault; thus, the danger posed by this attack is significantly decreased. In
addition, using encrypted packets for signals eliminates any possibility that a rogue control-
plane packet may get past the authorization check [45].
2.2.2. Countermeasures
To provide safety and information-related applications on the road, the vehicular ad
hoc network (Vanet) has recently received considerable attention in the smart transporta-
tion domain. Vanet delivers an infrastructure where vehicles moving on the road can use
communications to report traffic congestion, accidents, and road surface conditions to other
cars. Although Vanet is an excellent cyber–physical system [
46
], it has several security
and privacy problems, particularly location privacy. To be applied, they must enhance the
Vanets applications to preserve the identity and location privacy of cars. However, since a
hostile vehicle cannot be followed using a complete privacy-preservation strategy in a cyber
security scenario, most users would expect a conditional privacy-preservation approach to
safeguarding systems. Group signatures may be used to provide conditional privacy preser-
vation. However, the calculation costs are relatively high. Unlikable pseudo-ID techniques
may also produce dependent privacy preservation. However, revoking a malicious vehicle
would result in a lengthy revocation list. Unfortunately, any proposed method for verified
cater evocation does not enable forward unlikability. Forward unlikability is a challenging
criterion for Vanet systems. If a car is hacked and turns malevolent, the vehicle’s license
should be cancelled immediately. However, the vehicle’s previous communications and
positions (from before it was hacked) should be safeguarded and unlikable. To address
these issues, the authors of this research study [
47
] provide a lightweight conditional
privacy-preservation system that leverages basic hash-chain algorithms to allow accurate
identity monitoring by a trusted authority and quick local revocation verification on the
road. In Vanet systems, the suggested protocol addresses location privacy, conditional
privacy preservation, and forward unlikability.
In addition, novel security techniques are presented in this study [
48
] to enable safe
certificate revocation, which is regarded as one of the most demanding design challenges
in Vanet networks. Each vehicle that receives a message from another vehicle verifies
the sender’s certificate. The recipient verifies the sender’s certificate. When a sender’s
certificate is invalid, the recipient ignores the message. If the sender lacks credentials, the
receiver will report him to the road side unit and review the message. If the information
is correct, the road side unit (RSU) will issue a valid certificate. The road side unit will
issue an invalid certificate and add the vehicle to the revocation list otherwise. The RSU
replaces a misbehaving car’s valid certificate with an invalid certificate to indicate it should
be avoided. Multiple vehicles report to the road side unit that a car has a valid certificate
and is broadcasting incorrect data.
This research paper [
49
] presents a catalogue of potential solutions, each of which,
if put into practice, can dramatically cut the risk of cyberattacks on the communication
systems of connected cars in a vanet infrastructure. Five degrees of security architectures
may be chosen from the defense options that users can apply. However, cyber attackers
have a large terrain of assaults and objectives, and the variations between innocuous and
damaging are recorded in terms of the number of people killed and the amount of damage
done to transportation infrastructure.
Cryptography, zero-knowledge between communication vehicles, and authentication
methods with or without a trusted third party are all necessary breakthroughs; in reality,
they are inadequate [
50
–
52
], especially today, when more and more automated vehicles
are being put onto the roads, which need to cohabit with other types of motorized and
non-motorized traffic participants efficiently and safely. Autonomous cars do, however, run
the risk of traditional cyberattacks on the information and operation of the vehicle, as well
as a new breed of attacks surrounding things, such as ransomware, IoT attacks, and DDoS
attacks (connected vehicles drafted into Botnet Armies). Because of their interconnected
Appl. Sci. 2023,13, 790 10 of 36
nature, security risks are associated with the networks to which they are connected. This is
true regardless of the financial networks that process payments, roadside sensor networks,
electricity infrastructure, or traffic control features. The authors of this paper [
53
] propose a
method for designing safe and secure mixed traffic systems, including automated vehicles
and non-automated road users, such as pedestrians, bicyclists, and conventional vehicles.
This will allow the authors to model safe and secure cooperating automated vehicles and
road infrastructure. In addition, this method will enable the design of safer and more secure
automated vehicles and road infrastructure. The applicability of the suggested approach is
shown with the help of a typical scenario involving the interaction of an automated vehicle
with pedestrians at an intersection that does not have traffic signals.
The development of connected vehicles, which produce dynamic data through wireless
communications, has made it possible to automate vehicles to operate more effectively.
This is especially true in traffic signal control, which serves as the structural foundation
for the scheduling of traffic flow. On the other hand, wireless communication channels are
susceptible to cyberattacks and may constitute a significant risk to dynamic traffic signal
control systems. Attackers might manipulate the usual traffic flow to bring up extreme
traffic congestion. The authors of this work use deep reinforcement learning to create an
intelligent Sybil attack on a traffic intersection. In this attack, connected vehicles with fake
identities are optimally placed to change traffic signal timings by corrupting traffic data.
This work aims to highlight and exploit existing vulnerabilities in traffic signal control
systems. The findings indicate that this attack causes a sizeable increase in the time it takes
for vehicles to complete their journeys and results in catastrophic traffic congestion, mainly
if carried out for an extended period. This will lead to several serious issues, including
increased fuel consumption and air pollution in cities with a high population density. In
the face of such sophisticated assaults, the design assumptions behind present traffic signal
control systems have become increasingly suspect [54].
The authors of this research paper [
55
] establish an assessment methodology for cyber
attacks on autonomous cars using preexisting traffic flow models as the basis for their
work. They consider the percentage of cyber-attacked cars, the intensity and range of cyber
attacks, and transportation demand. Efficiency, safety, emissions, and fuel consumption
are used to evaluate the transportation system’s performance. Simulations show that as
the number of cyber-attacked vehicles and the severity of attacks increase, the negative
impact on traffic flow grows. This reduces capacity and increases rear-end collision risk, air
pollution, fuel consumption, etc. Cyberattacks on location rather than speed may cause
accidents and reduce traffic efficiency. Position-attacked traffic systems consume more
energy and produce more pollution. This research can be used to project future cyberattack
traffic, evaluate transportation systems, and manage automated highway systems from a
network security perspective.
However, as is easily understood, the big problem in smart mobility is the cyber
issues of mass transportation in which many people are carried within a single vehicle.
Specifically, the most serious difficulty is the cyber security of public transit [
56
,
57
]. Trains,
for example, are the most often used mode of transportation in a modern city, with millions
of daily passengers, as opposed to car transportation. Because of system and infrastructure
digitalization, the automation of railway processes, mass transit concerns, and expanding
linkages with external and multimodal systems, the railway industry is experiencing a
significant change in its operations, procedures, and infrastructure. Cybercriminals may
target ticket vending machines, passenger information screens, and the Wi-Fi infrastructure.
These systems are becoming more vulnerable to cyber attacks as they transition from
bespoke stand-alone systems to open-platform, standardized equipment built with com-
mercial off-the-shelf components and increased use of networked control and automation
systems accessible remotely via public and private networks. Many signals transmitted and
received over insecure communication links are critical to railway operations. Constant
monitoring, immediate notice of any departure from ordinary circumstances, and decisive
measures to resolve the issue allow for effective risk reduction and business continuity. Fur-
Appl. Sci. 2023,13, 790 11 of 36
thermore, uninterrupted and safe traffic operation depends on recognizing and addressing
threats to telecom, train management, and signaling systems as soon as possible. Complete
visibility and the capacity to identify and mitigate hazards as they emerge give a route to
reducing uncertainty and operational interruptions [58,59].
Though various studies on critical infrastructures have been conducted from the aspect
of cyber security, there has been little research conducted from the standpoint of cyber–
physical security in application areas such as the railway infrastructure. This is the first
complete empirical evaluation of the cyber–physical vulnerability of communication-based
train control systems [
60
]. The writers carefully analyze communication-based train control
and the cyber–physical vulnerabilities that may seize control of the train. They discover that
a man-in-the-middle assault combined with knowledge of railroad signaling may result
in substantial train crashes. They propose a countermeasure for communication-based
train control resilience to overcome the issue and meet these difficulties. The primary idea
behind this countermeasure design is to create a subsystem with a host that the attacker
cannot reach. The cable links the subsystem to the SDN switch. The SDN controller, on the
other hand, logically disconnects the link between the SDN switch and the subsystem. The
subsystem stays undiscovered due to the logical separation while the attacker seeks victims.
Consequently, during a man-in-the-middle attack, the subsystem may go undiscovered.
For the subsystem to warn the automated railway protection system of the attack scenario,
the SDN switch should detect ARP spoofing. The SDN switch continuously monitors ARP
messages and creates an IP-MAC list for ARP messages across the structure’s SDN switches.
They validate their findings by developing a realistic communication-based train control
testbed environment that yields promising outcomes.
In addition, this research [
61
] looks at the security of railway control equipment against
cyber or physical attacks. The authors offer a cyber–physical authentication approach that
combines an add-on security module with a cyber security protocol for device authenti-
cation and data transmission. A ‘hot swappable’ bump-in-the-wire security module adds
cryptographic capabilities to current control devices. The suggested system offered tamper
resistance by encapsulating the hardware in a tampered-detection box and using tamper-
resistant hardware to secure the cryptographic key. The device authentication protocol
secures server-to-control-device communication. Setup, first handshake, acknowledge-
ment/critical exchange, and data transmission make up the protocol. Due to storage needs,
the first handshake used RSA signatures, and the data transmission phase used AES with a
256-bit session key. Tests show that overall overhead has a minor impact on the railway’s
control device.
The authors offer a set of actions for enhancing cyber security and the information
power of railway management systems, with the instruments of risk engineering and
the knowledge gained from the information technologies serving as the foundation for
their recommendations. The criteria for the railway management system are outlined
in detail in work [
56
], which also provides a summary of the requirements that must be
met for the smart city concept. Additionally, in this paper [
62
], the authors provide the
bases for a combined safety and security risk assessment and analysis approach. This
approach reconciles the risk analysis processes used in both safety and security by making
relevant connections at different stages of the two methods and by adding cross-cutting
steps common to both safety and cybersecurity.
2.3. Smart Environment
A smart environment can make a significant contribution to the development of a
sustainable society. The smart environment combines appealing natural conditions, such
as climate, green spaces, and so on, with techniques for limited contamination, optimal
resource management, and environmental actions. It is also related to access to services
that improve the city’s quality of life and the facilities of public spaces on a broader scale.
In addition, it is associated with the city’s cleanliness, the initiatives that give life and
movement, and strengthening security in areas, such as local forests, lakes, etc. [63].
Appl. Sci. 2023,13, 790 12 of 36
A depiction of a smart environment monitoring application is presented in Figure 3.
Appl. Sci. 2023, 12, x FOR PEER REVIEW 13 of 38
Figure 3. Smart environment monitoring application [64].
A smart city can monitor energy consumption, air quality, building structural relia-
bility, and traffic congestion and address pollution or waste using technical management
tools. Thus, the sustainable and smart city considers using and producing green and re-
newable energies, more sustainable food production techniques, or the application of in-
novative technology to improve resource management (fuel, air, water, waste, etc.). Novel
environmental wireless sensor networks (WSNs) have the potential to monitor the natural
environment and potentially anticipate and detect natural disasters [65,66].
2.3.1. Cyber Threats or Attacks
WSNs are networks of autonomous sensing devices that monitor physical or envi-
ronmental factors such as temperature, pressure, sound, vibration, motion, or pollution at
several places. WSNs are multi-hop ad hoc self-organizing networks in which all nodes
interact wirelessly and use multiple routing protocols [67]. It works under circumstances
of limited bandwidth and performance. It is scalable and may accept more nodes or de-
vices at any moment. It is also adaptable, allowing for physical divisions, and all nodes
Figure 3. Smart environment monitoring application [64].
A smart city can monitor energy consumption, air quality, building structural relia-
bility, and traffic congestion and address pollution or waste using technical management
tools. Thus, the sustainable and smart city considers using and producing green and
renewable energies, more sustainable food production techniques, or the application of
innovative technology to improve resource management (fuel, air, water, waste, etc.). Novel
environmental wireless sensor networks (WSNs) have the potential to monitor the natural
environment and potentially anticipate and detect natural disasters [65,66].
2.3.1. Cyber Threats or Attacks
WSNs are networks of autonomous sensing devices that monitor physical or envi-
ronmental factors such as temperature, pressure, sound, vibration, motion, or pollution at
several places. WSNs are multi-hop ad hoc self-organizing networks in which all nodes
interact wirelessly and use multiple routing protocols [
67
]. It works under circumstances of
limited bandwidth and performance. It is scalable and may accept more nodes or devices
Appl. Sci. 2023,13, 790 13 of 36
at any moment. It is also adaptable, allowing for physical divisions, and all nodes may be
accessible through a centralized monitoring system [
68
]. Because it is wireless, it may be
used on a big scale and in various environmental applications or sectors. Furthermore, it
employs multiple security methods based on the underlying wireless technology, resulting
in a dependable network for specific users [69].
Smart cities can save energy and reduce carbon issues using WSNs. Specifically, it can
collect environmental factors through many wireless sensors and then return the informa-
tion to the backend monitoring server. This study [
70
] presents a WSN using ecological
sensors and controllers to adjust the energy consumption of electrical appliances. Because
a plethora of wireless nodes are exposed to physical or logical access in remote urban areas,
the authors performed a massive simulation of DoS attacks or external damage by human
manipulations. The authors used a sophisticated analysis of various packet loss patterns
to identify the potential damage and examine the abnormality. After identifying damage
by the logical or physical attack, each node is used by the different queue management
models to collect environmental data.
It is difficult to approach or work at the WSN since it operates in a complicated setting.
Because nodes are open, they are susceptible to numerous assaults. Traditional security
systems will also mistake nodes deployed in a complex environment with poor-quality
connections or poorer conditions (less energy or a higher workload) for malicious nodes.
In WSN, the trust and reputation model may be employed to mitigate the harm caused by
malicious nodes. However, trust and reputation models have a sizeable false-positive rate
since a node with less reputation is evaluated as undesirable owing to the communication
context. This study [
71
] provides trust and reputation-based harmful node detection
techniques with environmental factors to prevent malicious nodes from interfering with or
selectively forwarding attack nodes. Machine learning’s linear regression and combining
node energy, data volume, number of nearby nodes, node sparsity, and other deterministic
characteristics can solve environmental parameters. Using environmental parameters,
benchmark trust is estimated. The Gaussian radial basis function is simplified to compare
the benchmark and cycle reputation sequences. Environmental settings provide three
reputation intervals and an adoption threshold span to detect malicious nodes based on
work environment and node statuses. The simulations show that factors increase malicious
node detection by 1% and reduce false positives by 1%.
To communicate outside of the wireless communication zone, WSN employs mobile
nodes. Wireless ad hoc network routing protocol attacks degrade network performance and
dependability. Malicious nodes advertise the shortest route between source and destination
in active black hole attacks on wireless networks, resulting in routing table alterations
and packet loss. Self-security management is a hot topic in WSN-related environmental
applications. For example, this paper [
72
] provides the grouped black hole attack security
model (GBHASM), which prevents grouped hostile nodes from advertising the shortest
route between source and destination, preventing routing table alterations and packet loss.
The GBHASM proposed is separated into two components. The first module describes how
a new node will join the network, while the second handles communication.
The joining request is received from the new joining node in the replay. It sends
membership acknowledgement and waits for replication approval. If the request is not
accepted within a specific time frame, it will be rejected; if approved, the demand for its
details will be delivered. The same procedures will be repeated till the process is completed.
Information received from a new joining node is recorded in the database, given a new
node code, and the updated node code table is propagated on the network. The second
model deals with network communication activities. After joining the network, the node
sends out queries for the quickest network route. Every node will compare the node code,
and if the key matches within a specific time frame, information about the packet will be
revealed. Otherwise, the time-to-live package will be sent to the next node.
Appl. Sci. 2023,13, 790 14 of 36
2.3.2. Countermeasures
Although prevention and monitoring techniques may lower the risk of cyber assaults,
the residual risk in vital infrastructures or services might still be unacceptable. Resilience,
or a system’s capacity to survive evil occurrences while retaining adequate operation, is a
crucial attribute of such systems. While numerous resilience indicators have previously
been proposed, there are limited experimental data on the cyber security of CPSs. This
study [
73
] aims to provide a model-free, quantitative, and general-purpose assessment
approach for extracting resilience indices from data sources such as system logs and
process logs. The authors evaluate four resilience indices from a broad range using an
actual wastewater treatment plant model and modeling assaults that interfere with a vital
feedback control loop. The findings reveal that although the selected indexes varied in their
behavior and susceptibility to certain assaults, they can all summarize and extract valuable
information from large system logs. The proposed method includes deriving performance
indicators from observable data without understanding the system dynamics.
Waste management and recycling are critical to remaining sustainable and clean in
contemporary metropolitan settings. Solid waste management, disposal, and recycling are
all difficulties in many major cities across the globe. Combining IoTs with deep learning
provides a modular approach for data classification and real-time analysis. This article [
74
]
depicts an effective smart waste management and classification system based on IoT and
deep learning. The study proposes a microchip-based trash can with a fast waste collection
system. IoT provides real-time data control in the recommended data-monitoring system.
Smart trash management and categorization include a convolutional neural-network-based
algorithm. This waste-collection facility will use trash classification to increase recycling.
This system offers waste collection, management, and categorization.
Modern technologies enable water distribution systems (WDSs) to provide improved
water supply, storage, distribution, and recycling services. They help with real-time
monitoring, automation, and management. However, the limitations of these technologies
expose the WDS to cyber–physical threats. The primary aim of cyber–physical assaults is
to interrupt regular operations and tamper with crucial data, negatively influencing the
WDS. As a result, it is critical to design and deploys solutions to improve WDS security
by detecting and mitigating cyber–physical assaults. The authors of this research [
75
]
thoroughly investigate typical cyber–physical assaults and common detection strategies
for the WDS. They contrast assaults and detection approaches, focusing on concepts,
methodologies, evaluation findings, benefits, limits, etc.
The increasing number of successful and attempted attacks on critical infrastructures,
such as power grids and water treatment plants, has resulted in an urgent need to develop
and implement methods for detecting such attacks, which state actors or insiders in the
targeted organization frequently carry out. This research [
76
] aims to provide a case study
of an infected wastewater treatment plant (WTP) that used a live memory dump acquisition
Imager. The forensic carving procedure is removed in bulk, and features are extracted
from the memory dump. In addition, this study [
77
] emphasizes one method to identify
assaults that compromise one or more actuators and sensors in a plant by successfully
infiltrating the plant’s communication network or accessing the plant computers directly.
This technique, known as distributed attack detection (DAD), may detect assaults in real
time by spotting irregularities in the behavior of the physical process in the plant. The
use of monitors that are actual implementations of the invariants obtained from the plant
architecture is how anomalies are discovered. Each invariant must remain valid during
the whole plant operation or while the plant is in a specific condition. A functioning water
treatment facility was used in an experiment to evaluate the efficiency of DAD, and it was
proven to be successful at detecting sneaky and coordinated assaults. Additionally, this
study [
78
] aims to provide a technique for enhancing operational security in a wastewater
treatment plant and to demonstrate how this approach can be used in a particular setting.
The motivation stems from the requirement to comprehensively understand security
events or attacks on a network and information about the intensity and propagation pattern.
Appl. Sci. 2023,13, 790 15 of 36
In parallel, this study [
73
] suggests a cyber-security monitoring system that connects time-
series event data, visually [
74
] depicting security occurrences. It provides a predictive
prediction of probable circumstances based on established situations. Furthermore, it
may assist business choices by identifying or comprehending the link between computer
equipment and their business/information technology services.
In recent years, the smart energy grid has steadily become the usual development trend
in the world’s power business. It is an improvement to the old system that incorporates
technology and communication into the present grid. This results in a more efficient grid
that decreases energy demand peaks and can efficiently integrate renewable resources
(at naturally varying levels) into its network. To increase their security, smart grids have
included physical control, data encryption, and authentication technologies. However,
there is still a shortage of timely and efficient detection tools to keep the grid safe from
unwanted breaches. In response to this issue, a machine-learning-based methodology for
detecting smart grid DoS assaults was developed in this study [
79
]. The model initially
gathers network data, picks features, uses principal component analysis (PCA) to reduce
data dimensionality, and then employs the support vector machine (SVM) algorithm to
identify abnormalities. The study exploits the attack vulnerabilities of smart meters and
data servers to add data collection and intrusion detection modules between smart meters
and data servers, aiming at the design structure of the smart grid. In the smart grid, real-
time data capture and detection are possible. When DoS attack activity is recognized, the
alarm system is initiated to handle the alert.
Cyber security must be a primary priority for electric power providers installing smart
meters and smart grid technologies. Despite the well-known benefits of smart meters,
how and to what degree cyber assaults might disrupt smart meter functioning and remote
data collecting about power use from client locations is unclear. To answer these issues,
this study [
80
] tested a commercial-grade smart meter in a controlled lab and assessed its
operational integrity under cyber-attack situations. In addition, the false data injection
attack (FDIA) is a way of disrupting the security of the power system based on meter
measurement. FDIA detection researchers are now focused on detecting its existence. FDIA
location information is also critical for power system security. Finally, in this study [
81
],
identifying the meter’s FDIA is seen as a multi-label classification task. Each label denotes
the current condition of the respective meter. The multi-label decision tree approach is used
as the classifier in the ensemble model to discover the precise position of the FDIA. This
approach does not need power topology information or statistical knowledge assumptions.
The suggested method’s performance is validated by numerical tests using the IEEE-14
bus system.
2.4. Smart Lining
Smart living is intended to optimize and manage facilities. It emphasizes one of the
primary goals of the sustainable and smart territory, which is to enhance the quality of
life of its residents. The smart living axis is built on three key pillars: civic safety, social
cohesion, and tourist attraction.
It is a solution that maximizes the city’s infrastructure while improving people’s
quality of life. It allows for real-time control, forecasting, and optimal asset optimization
and management. The following are some smart living applications [82]:
1.
Detectors of fire: It is feasible to monitor, detect, and prevent fires in the urban
environment with this 24/7 program. Furthermore, the detection may approach the
various sources of fire efficiently to manage the fire more effectively.
2.
Intelligent video surveillance: to improve public safety and to use predictive analytics
to optimize traffic flow and citizen safety.
3.
Sports facility management: Smart living solutions include controlling capacity and
performing centralized administration of sports facilities. It is also beneficial for
making judgments based on historical data, identifying deficiencies or requirements,
and implementing management and infrastructure upgrades.
Appl. Sci. 2023,13, 790 16 of 36
4.
Smart home automation: It monitors and regulates home smart applications such as
temperature, humidity, electric equipment, security, and so on in real-time.
Smart living ICT utilities allow operations to decrease resource overconsumption, such
as water and gas while increasing economic development and environmental protection. A
depiction of a smart living scenatio is presented in Figure 4.
Appl. Sci. 2023, 12, x FOR PEER REVIEW 17 of 38
4. Smart home automation: It monitors and regulates home smart applications such as
temperature, humidity, electric equipment, security, and so on in real-time.
Smart living ICT utilities allow operations to decrease resource overconsumption,
such as water and gas while increasing economic development and environmental pro-
tection. A depiction of a smart living scenatio is presented in Figure 4.
Figure 4. Smart living Scenario.
2.4.1. Cyber Threats or Attacks
The linked smart house poses a variety of security risks. To begin with, individual
smart living gadgets may not be secure. Some IoT home devices are hurried to market,
and their security may be compromised. In certain circumstances, user manuals fail to
address privacy issues or provide sufficient information to ensure the device’s security.
Baby monitors and security cameras, for example, have been hacked, enabling hackers to
view inside a home [83].
Intruders may access any data stored on an insecure home network. An intruder may
monitor device use to determine when users are away. IoT data are at risk if the main
internet account controls the home network. Any flaw could expose email, social media,
and bank account information. Insecure IoT devices must not compromise the home net-
work’s security. Many customers control their smart homes via smartphone, making it a
valuable database for hackers [84].
As follows from the above, it is critical to describe and comprehend the direction and
development required to guarantee that, as smart home systems become more prevalent,
the security and functionality of these systems are maintained. Form this spirit, the goal
of this study [85] is to identify the hazards associated with smart home systems and re-
search ways to reduce such risks. Additionally, it provides a comprehensive analysis of
the techniques currently used by intruders, the reasons for adopting these methods, and
what might be done differently to enhance smart home security. This paper [86] also pre-
sents and discusses the threats that can affect smart living systems and define the require-
ment to improve secure communication between smart home devices and applications
that remotely control the home devices.
Figure 4. Smart living Scenario.
2.4.1. Cyber Threats or Attacks
The linked smart house poses a variety of security risks. To begin with, individual
smart living gadgets may not be secure. Some IoT home devices are hurried to market,
and their security may be compromised. In certain circumstances, user manuals fail to
address privacy issues or provide sufficient information to ensure the device’s security.
Baby monitors and security cameras, for example, have been hacked, enabling hackers to
view inside a home [83].
Intruders may access any data stored on an insecure home network. An intruder
may monitor device use to determine when users are away. IoT data are at risk if the
main internet account controls the home network. Any flaw could expose email, social
media, and bank account information. Insecure IoT devices must not compromise the home
network’s security. Many customers control their smart homes via smartphone, making it a
valuable database for hackers [84].
As follows from the above, it is critical to describe and comprehend the direction and
development required to guarantee that, as smart home systems become more prevalent,
the security and functionality of these systems are maintained. Form this spirit, the goal of
this study [
85
] is to identify the hazards associated with smart home systems and research
ways to reduce such risks. Additionally, it provides a comprehensive analysis of the
techniques currently used by intruders, the reasons for adopting these methods, and what
might be done differently to enhance smart home security. This paper [
86
] also presents
and discusses the threats that can affect smart living systems and define the requirement
to improve secure communication between smart home devices and applications that
remotely control the home devices.
Appl. Sci. 2023,13, 790 17 of 36
Vulnerabilities in IoT-based systems provide security risks and obstacles for smart
applications. One of the most significant impediments to IoT-based systems was identified
by the low-level security provided. The smart home environment presents novel security,
authentication, access control, and privacy concerns due to its internet-connected, dynamic,
and diverse nature. The IoT-based smart environment requires an attack model and a risk
management framework to improve information security and integrity. This research [
87
]
provides a finite state automata-based attack model for investigating smart home-based
security assaults and assessing their effect using the suggested risk management frame-
work for mitigating IoT smart-home-related attacks. An examination of the typical attack
behavior and the risk-management framework demonstrates that the proposed approach
is feasible and effective and can be used in many smart home applications.
IoT implementation in the smart home sector is complicated since the devices utilized
in such platforms vary in size and computing capacity. The capacity to impose security on
such machines depends on how well the authentication procedures are carried out. Against
this backdrop, this paper [
88
] is designed to thoroughly examine possible authentication
risks and attacks on IoT, specifically in the smart home sector. The significant concepts
offered in this study on potential authentication risks and assaults on IoT in Smart home
applications are primarily influenced by a careful literature assessment of relevant work
in IoT.
2.4.2. Countermeasures
This research looked at the system architecture of a smart home ecosystem, vulner-
abilities, potential assaults, requirements, and post-attack settings [
89
]. We propose an
architecture analysis and design language tool model for the smart home architecture,
which is then visualized using a complex graph tool against a security policy. The attack
graph highlights the need to address security considerations while creating smart home
systems and identifying potential threat landscapes.
This article [
86
] presents the design and implementation of a safe framework that
provides flexibility and security for smart home systems based on CPS and IoT based on
the notion that the primary goal of home automation is to control home devices from a
single place. As a result, the authors suggest a safe design that protects the system from
external internet infections. They address home automation security concerns by installing
a secure firewall software solution. A secure firewall identifies and warns the user of
specific security vulnerabilities before launching its mitigation technique. Internal security
additionally offers encryption for communication and protects the home automation system
from unethical acts. This technology (cypher firewall) determines the user privacy problem
since it does not allow external threats. Users may monitor smart home activity by attaching
static IP addresses to the system. Users may connect to a home coordinator already tied to
home automation through cellular internet. Users may turn on/off their TV, door, lights,
heat radiator, air conditioning, and water appliances using their connection.
The comparatively inadequate information security of smart home system (SHS)
devices may jeopardize consumers’ privacy. The authors of this paper [
90
] propose a
novel block data structure based on homomorphic encryption to record the SHS device
information transaction. This study presents a homomorphic consortium blockchain for
SHS-Sensitive Data Privacy (HCB-SDPP). To validate SHS operational nodes and transac-
tions, the authors add verification nodes. Using HCB-SDPP, they create a Par-lier-based
algorithm for privacy protection. To validate the HCB-SDPP architecture, they encrypt
gateway peer data and submit them to the consortium blockchain. They assess data secu-
rity after homomorphic encryption. The authors target various peers on the consortium
blockchain in the experiment using HCB-SDPP. If these nodes are vulnerable, the model
is affected. The simulation results suggest that HCB-SDPP protects client privacy better
than SHS.
Wireless home alarm systems are becoming more popular, but their security has
received little attention. Existing attacks on wireless home alarm systems use networking
Appl. Sci. 2023,13, 790 18 of 36
protocol flaws while ignoring issues caused by the physical components of IoT devices.
The authors of this study [
91
] demonstrate novel event-elimination and event-spoofing
attacks against commercial wireless home alarm systems by interfering with the reed
switch in practically all COTS alarm sensors in this research. In both assaults, the external
adversary controls the state of the reed switch with his magnet to either delete valid alerts
or spoof false warnings. The authors also demonstrate a novel battery-depletion assault
using programmed electromagnets to quickly and quietly drain the alarm sensor’s battery,
intended to last a few years. Extensive tests on a sample ring alarm system indicate the
effectiveness of these assaults.
On the other hand, several inspired smart living applications fulfil privacy and security
standards [
83
]. The primary purpose of this proposed project is to use new IoT technologies
to enable the senior population to self-manage their health and remain active, healthy,
and independent for as long as feasible in a smart and safe living environment. An open-
source, comprehensive IoT ecosystem is proposed. It includes the following processes:
data gathering, data transportation, data integration, processing, manipulation, computing,
visualization, data intelligence and exploitation, data sharing, and data storage. This
unique cloud-based IoT ecosystem serves as a one-stop-shop for integrated smart IoT-
enabled services to assist elderly persons (65 and older) who live alone at home (or in
care homes). Another breakthrough is this system’s design and implementation of an
integrated IoT gateway for wellness wearable and home automation system sensors with
diverse connection protocols. The smart living system and services address smart health
and care, smart quality of life, and the social community. The system is developed using
the user-centered design process to enable active user interaction throughout the project
lifecycle and relevant standards and compliances (e.g., security, trust, and privacy) that are
followed to increase user-friendly adoption.
Access-control rules in smart buildings are becoming more dependent on context,
such as who is taking action, if there is an emergency, or whether an adult is around. The
extensive literature on context sensing might be used to provide contextual access control,
but it mostly overlooks threats, adversaries, and privacy. The authors of this work [
92
]
reassess the literature on home context sensing from the standpoints of security and confi-
dentiality. They describe a unique threat model in smart homes focusing on non-technical
adversaries’ capabilities. In this model, replay, mimicry, and shoulder-surfing assaults are
significantly more common. They also synthesize circumstances pertinent to home access
control, matching them to existing sensors. They then organize the sensing literature to
provide a decision framework for home context sensing that considers security, privacy,
and usability. Using their approach, they discover that present sensors do not adequately
reduce potential hazards in houses. Some sensors are vulnerable to primary threats, such
as physical denial-of-service attacks, making it simple to circumvent restrictions based on
the lack of a characteristic. Many sensors capture more data than necessary and are useless
for all user groups or scenarios.
Simultaneous advances in the internet of things and machine learning have resulted in
exciting multidisciplinary applications, such as classification tasks based on data provided
by smart devices for different applications, such as resource allocation, security, and activity
categorization. However, such applications may be vulnerable to adversarial scenarios.
The authors of this research [
93
] create a white-box adversarial attack technique to produce
adversarial instances for data acquired from smart meters placed in residential homes and
show that their statistical features are indistinguishable from actual data points. Adversarial
machine learning, a method that uses false data to trick algorithms, is a developing danger
in AI and machine learning research. The most typical reason is to cause a machine-
learning model to malfunction [94]. An adversarial attack might include training a model
with erroneous or misleading data or injecting deliberately crafted data to confuse an
already trained model. The attack technique focuses primarily on deep learning-based
models used in smart home device categorization. Because the adversarial data points
are statistically indistinguishable from the actual data points, non-machine-learning-based
Appl. Sci. 2023,13, 790 19 of 36
solutions may be unable to address the issue given by hostile instances. The suggested
strategies’ efficacy is proved using the publicly accessible United Kingdom-Domestic
Appliance-Level Electricity smart-meter dataset.
2.5. Smart Healthcare
Quality, results, and value are the outcomes of technological advancement in the health
industry. Patients need excellent and personalized services [
95
,
96
]. Thus, it is critical to
invest in this area. Digital healthcare is a movement that entails leveraging new technology
to increase support while keeping costs as low as feasible [97,98].
A depiction of a smart healthcare scenario over blockchain is presented in Figure 5.
Appl. Sci. 2023, 12, x FOR PEER REVIEW 20 of 38
learning-based models used in smart home device categorization. Because the adversarial
data points are statistically indistinguishable from the actual data points, non-machine-
learning-based solutions may be unable to address the issue given by hostile instances.
The suggested strategies’ efficacy is proved using the publicly accessible United King-
dom-Domestic Appliance-Level Electricity smart-meter dataset.
2.5. Smart Healthcare
Quality, results, and value are the outcomes of technological advancement in the
health industry. Patients need excellent and personalized services [95,96]. Thus, it is criti-
cal to invest in this area. Digital healthcare is a movement that entails leveraging new
technology to increase support while keeping costs as low as feasible [97,98].
A depiction of a smart healthcare scenario over blockchain is presented in Figure 5.
Figure 5. Smart healthcare scenario over blockchain.
Smart healthcare entails the adoption of new goods and technology for diagnosis and
treatment, a more considerable interchange of information across parties, a more active
role for patients during treatment, and improved clinical data management [99,100]. Hu-
man and non-human players in smart healthcare include physicians, patients, hospitals,
and research organizations. Smart healthcare strives to make patient care safer, better, and
more manageable. IoT connection is transforming healthcare by linking patients and
healthcare professionals in novel ways [101]. Wearables, skin sensors, home-monitoring
tools, and other IoT-connected gadgets allow deeper medical insights into symptoms and
health patterns, new degrees of remote care, and more control over patients’ care and
treatment. Like those used in other IoT-connected applications, sensors are critical in gath-
ering and analyzing real-time patient data. Artificial intelligence (AI), the IoT, the medical
internet of things (MIoT), edge computing, cloud computing, big data, and next-genera-
tion wireless communication technology are at their heart [102]. This allows healthcare
practitioners to spend more time with patients and treating diseases and less on logistics.
2.5.1. Cyber Threats or Attacks
Figure 5. Smart healthcare scenario over blockchain.
Smart healthcare entails the adoption of new goods and technology for diagnosis and
treatment, a more considerable interchange of information across parties, a more active role
for patients during treatment, and improved clinical data management [
99
,
100
]. Human
and non-human players in smart healthcare include physicians, patients, hospitals, and
research organizations. Smart healthcare strives to make patient care safer, better, and more
manageable. IoT connection is transforming healthcare by linking patients and healthcare
professionals in novel ways [
101
]. Wearables, skin sensors, home-monitoring tools, and
other IoT-connected gadgets allow deeper medical insights into symptoms and health
patterns, new degrees of remote care, and more control over patients’ care and treatment.
Like those used in other IoT-connected applications, sensors are critical in gathering and
analyzing real-time patient data. Artificial intelligence (AI), the IoT, the medical internet of
things (MIoT), edge computing, cloud computing, big data, and next-generation wireless
communication technology are at their heart [102]. This allows healthcare practitioners to
spend more time with patients and treating diseases and less on logistics.
2.5.1. Cyber Threats or Attacks
Smart health is an important field that continually analyzes patients’ health, alternative
treatments, and cutting-edge disease-fighting technology. The purpose of smart health is to
provide individuals with medical services at any time and from any place. Smart health
monitoring devices are often connected through wireless networks, which are vulnerable to
Appl. Sci. 2023,13, 790 20 of 36
cyber threats. However, various risks may endanger these health monitoring applications
and systems [
103
,
104
]. These include denial-of-service (DoS) attacks, fingerprint and
timing-based eavesdropping, router attacks, select and forwarding attacks, sensor attacks,
and replay attacks [
105
,
106
]. In this paper [
107
], the authors investigate the consequences
of these attacks on health monitoring systems and recommend some interventions based
on their research findings.
The most challenging aspect of smart health apps is protecting data from numerous
assaults while using simple approaches and algorithms. Given the security problems associ-
ated with implementing smart health apps as the primary data collecting and transmission
source, cyber threats are categorized to create a viable defense strategy. This research [
5
]
contributes to the analysis of security and privacy in the context of smart cities for health-
care applications in two ways. On the one hand, an overview of several IoT applications
and their cyber vulnerabilities is provided. On the other hand, a complete assessment of
potential solutions to the issue of cyber assaults is given.
In recent years, smart healthcare has gained popularity. Because of the data it collects,
a more secure mechanism is required to maintain security and privacy. As a result, these
techniques may also guarantee security and privacy in smart health. This review paper
aims to assess individuals’ concerns with security issues in their smart homes and to start
a debate about how healthcare equipment that comes packaged with future houses is
susceptible to cyber attacks that result in data breaches. Blockchain is proposed in this
study [
108
] to increase security and privacy in smart healthcare. The proposed platform
uses blockchain technology and considers the client’s control over the healthcare data,
implying the ability to share data with a specific association or person on a case-to-case
and field basis. Using this platform, the writers discussed emerging blockchain technology
and how its components may help healthcare flourish while maintaining total security.
Humans benefit from the fast progress of the MIoT connected with biosensors in
various ways, including smart healthcare systems (SHeSs). The combination of MIoT
devices and the increasingly networked nature of the healthcare environment enables
healthcare providers to provide more efficient and effective emergency and preventative
medical services to their patients. SHeS offers several chances for healthcare professionals
and institutions to monitor patients’ health remotely. The health statistics acquired by SHeS
are kind. However, SHeS exposes patients’ health data to various assaults.
2.5.2. Countermeasures
The most complicated difficulties in smart healthcare systems are ensuring patient
health data confidentiality and privacy. This paper [
109
] explores health data confidentiality,
MIoT healthcare security concerns, and the rules and regulations involved in establishing
a smart healthcare system. It also describes the many prevalent principles and assaults
exposed to corporate digital assets and patients’ health information, as well as the necessary
solutions for overcoming the present obstacles, such as a cryptographic function and a
communication protocol.
For example, this work [
88
] provides a complete overview of possible authentication
risks and attacks on IoT healthcare devices in the Smart healthcare area. Furthermore,
utilizing a hybrid cryptographic technique, the authors of [
110
] established a secure cloud
storage solution for healthcare data. A symmetric algorithm encrypts data, while an
asymmetric algorithm encrypts keys. The performance and security of the proposed
approach were measured and compared to a well-known current technology. Because it is
based on a modular exponentiation process, the RSA method often performs poorly. As a
result, the authors used the Montgomery modular multiplication technique to enhance the
RSA implementation. Blowfish encryption is used when storing health-related data in the
cloud, and keys are handled using the improved RSA technique. This hybrid technique
provided advantages such as quick encryption, large prime numbers for essential creation,
and efficient key management. The simulation results reveal that the suggested hybrid
Appl. Sci. 2023,13, 790 21 of 36
technique’s encryption and decryption time is faster than other approaches examined
for comparison.
Important points to discuss when exchanging information in a smart health system
dealing with critical patient data are communicating across institutions and safeguarding
patients’ private data. This work [
111
] proposes a method for saving image-type data
using visual cryptography and distributing the data utilizing secretive sharing using
practitioners’ passwords. However, if penetrated, the underlying infrastructure might result
in private data leaks and the destruction of healthcare records dependent on the control
commands supplied by the attacker. The authors of this paper [
112
] concentrate on several
degrees of security associated with the storage and transmission of healthcare information.
Furthermore, they test some of the suggested approach’s relevant characteristics using the
access control policy testing tool to establish its practicality and examine the state of the
art in the subject. However, because the present record management system cannot fully
handle privacy and integrity, the health sectors nowadays use blockchain technology to
store health data in a more safe, confident and decentralized manner.
This study [
113
] offers a blockchain architecture for electronic health records to safe-
guard private data based on the elliptic curve cryptography algorithm. In parallel, this
study [
114
] proposes a realistic solution based on the unique characteristics of blockchain,
where the distributed ledger technology is thought to be unbackable. The authors created
a blockchain model to safeguard data security and privacy, assure data provenance, and
give patients total control over their health information using the smart contract feature, a
programmable self-executing protocol operating on a blockchain. This concept delivers a
patient-centric procedure by customizing data segmentation and creating permitted lists
for physicians to access their data. It assesses the model’s feasibility, stability, security,
and robustness. In addition, this article [
115
] offers a permission Ethereum blockchain
that connects hospitals and patients all over the globe. The proposed system employs
symmetric and asymmetric key encryption to enable safe storage and selective access to
records. It gives patients total control over their health information and allows them to
grant or deny access to their records to a hospital. The authors stored records using the
interplanetary file system (IPFS), which has the benefit of being dispersed and assuring
record immutability. The suggested methodology also keeps illness data without invading
any patient’s privacy.
The rising availability of healthcare data necessitates the precise analysis of illness
diagnosis, progression, and real-time monitoring to enhance patients’ therapies. Machine
learning (ML) models are used in this context to extract significant characteristics and
insights from high-dimensional and heterogeneous healthcare data to identify various
illnesses and patient behaviours in a SHeS. However, recent studies reveal that ML mod-
els employed in different application areas are susceptible to adversarial assaults. This
work [
116
] describes a novel adversarial method for exploiting the ML classifiers used in
an SHeS. An attacker with a rudimentary understanding of data distribution, the SHeS
model, and an ML algorithm may launch both targeted and untargeted assaults. Their
attack employs five different adversarial ML algorithms to carry out various malicious
behaviours on an SHeS (e.g., data poisoning, misclassifying outputs, and so on). Using
these adversarial capabilities, the authors modify medical device readings resulting from
the SHS to change the patient status (disease-affected, normal condition, activities, etc.).
Furthermore, according to an adversary’s training and testing phase capabilities,
the system undertakes white and black box attacks on an SHeS. They also assess the
effectiveness of their work in various SHeS settings and medical equipment. Their rigorous
study demonstrates that the suggested adversarial approach may severely reduce the
effectiveness of an ML-based SHeS in properly recognizing illnesses and normal patient
behaviours, resulting in incorrect treatment.
Appl. Sci. 2023,13, 790 22 of 36
2.6. Smart Economy
A sustainable and smart city is a fertile platform for innovation and new business
models [
117
]. This vision is supported by sustainable entrepreneurship and the circular
economy. These innovative approaches promote local and global financial ecosystem
linkages while fostering long-term economic competitiveness. The smart economy concept
is a prosperous economic prototype built on technology innovation, resource efficiency,
sustainability, and high social welfare. It encourages innovation and new entrepreneurial
activities while increasing productivity and competitiveness with the overarching objective
of enhancing inhabitants’ quality of life [118].
A depiction of a smart economy in smart cities is presented in Figure 6.
Appl. Sci. 2023, 12, x FOR PEER REVIEW 23 of 38
2.6. Smart Economy
A sustainable and smart city is a fertile platform for innovation and new business
models [117]. This vision is supported by sustainable entrepreneurship and the circular
economy. These innovative approaches promote local and global financial ecosystem link-
ages while fostering long-term economic competitiveness. The smart economy concept is
a prosperous economic prototype built on technology innovation, resource efficiency, sus-
tainability, and high social welfare. It encourages innovation and new entrepreneurial ac-
tivities while increasing productivity and competitiveness with the overarching objective
of enhancing inhabitants’ quality of life [118].
A depiction of a smart economy in smart cities is presented in Figure 6.
Figure 6. Smart economy scenario in smart cities.
This technology-driven, interconnected system employs ICT applications for eco-
nomic progress, urban planning, and public health improvement. It combines enhanced
creativity with improved production, efficiency, and competitiveness. Several new flexi-
ble kinds of labor and start-ups distinguish it. A smart economy is projected to produce
more goods and services using less energy, emitting less pollution, and offering social
benefits [119]. For example, in Jakarta, a smart city, the smart economy idea being applied
aims to encourage an entrepreneurial and innovative spirit in society to attain high
productivity. Jakarta also has several smart economy projects [120,121] that benefit its in-
habitants. Among these programs are the following [122–124]:
1. JakPreneur: Jakarta’s MSME development initiative encourages the creation and col-
laboration of an entrepreneurial ecosystem. MSME actors will receive training,
coaching, marketing, and even instruction on obtaining funding via JakPreneur.
2. JakPangan: provides information on the cost of Jakarta’s primary commodities.
3. JakNaker Platform: a portal designed to make it simpler for citizens to find jobs.
4. JakOne Pay: a non-cash payment option developed in partnership with banks [9].
Figure 6. Smart economy scenario in smart cities.
This technology-driven, interconnected system employs ICT applications for economic
progress, urban planning, and public health improvement. It combines enhanced creativity
with improved production, efficiency, and competitiveness. Several new flexible kinds of
labor and start-ups distinguish it. A smart economy is projected to produce more goods
and services using less energy, emitting less pollution, and offering social benefits [
119
]. For
example, in Jakarta, a smart city, the smart economy idea being applied aims to encourage
an entrepreneurial and innovative spirit in society to attain high productivity. Jakarta also
has several smart economy projects [
120
,
121
] that benefit its inhabitants. Among these
programs are the following [122–124]:
1.
JakPreneur: Jakarta’s MSME development initiative encourages the creation and
collaboration of an entrepreneurial ecosystem. MSME actors will receive training,
coaching, marketing, and even instruction on obtaining funding via JakPreneur.
2. JakPangan: provides information on the cost of Jakarta’s primary commodities.
3. JakNaker Platform: a portal designed to make it simpler for citizens to find jobs.
4. JakOne Pay: a non-cash payment option developed in partnership with banks [9].
5.
JakLingko Card: The JakLingko card may pay for many kinds of transportation (buses,
microbuses, railways, etc.).
Appl. Sci. 2023,13, 790 23 of 36
To attain the degree of smartness that cities manage, smart cities are often tied to
development initiatives. Several studies look at intelligent smart city performance utilizing
various approaches and assessment criteria. Although there is no way to perform such an
assessment, the smart economy is essential in assessing smart cities. The smart economy
was a significant feature in determining smart cities in 25 of the 30 studies examined
between 2015 and 2020. The authors of this research [
117
] underline the relevance of the
smart economy component in smart city development and demonstrate how it is assessed
and evaluated in various evaluation methods. Furthermore, it delves into smart economy-
related metrics utilized in multiple evaluation methods. The authors use a theoretical
approach combined with quantitative and qualitative data to investigate similarities and
relationships among the best-performing cities in the smart economy.
To accomplish urban management services, business survival growth, and inhabitants’
productive lifestyle, a smart city is the application of a new generation of information
technology. The smart economy boosts core competitiveness and may give citizens various
economic options. Using China as an example, this paper [
125
] proposes a smart city
development path based on the current state of smart city construction: use Internet
technology to build big public data, strengthen the structure of digital infrastructure
projects, ultimately mine data, lay a good technical foundation for smart city construction,
integrate urban development with the Internet, and gradually promote harmonious town
development. Moreover, this study [
126
] proposes a new service-oriented manufacturing
business model called a smart linked product–service system (PSS) against the rapid rise of
customized service demand, the digitalization of goods and services, and the socializing
of service resources. The issue of CPS-oriented smart connected products and associated
service resources is explored from the service flow and product serviceability, as well as the
smart corresponding product service system design and socialized service crowdsourcing
setup. It is divided into three sections: analysis of personalized service demands using
service flow design and product minimum service capacity modeling method to meet
service requirements; CPS-embedded web services modular design method for smart
connected product; and community construction of service resources using federated
learning and service order-driven social crowdsourcing configuration. The objective is to
create a new generation of service-oriented manufacturing models that are smart, connected,
efficient, and adaptable.
Growing a local economy based on sharing data from IoT devices and other open data
that can be utilized in apps to better the lives of its residents is one way a city might become
smarter. The authors of Ref. [
127
] investigate how blockchain and other distributed ledger
technologies may be used to build a decentralized data marketplace. They explore the
potential advantages of such a decentralized architecture, define several features that such a
decentralized marketplace should include, and demonstrate how they may be incorporated
into a holistic system. They also describe a basic, smart contract implementation of a
decentralized registry where data owners may publish items for prospective purchasers
to retrieve.
There are several hurdles to overcome to advance this decentralized marketplace.
These are some examples:
1.
Managing system complexity: With so many moving parts and components, the
decentralized marketplace system may become fragmented or difficult to scale; how
can this be avoided? Maintaining a tight foundation may hinder scalability.
2.
Economic incentives and centralization: Without sufficient financial incentives for
all parties involved, the decentralized marketplace may fail to operate successfully.
It may be required to carefully construct the incentives so that additional decision-
making power and data do not get concentrated in the hands of specific parties,
thereby distorting rankings and recommendations in unjust ways.
Appl. Sci. 2023,13, 790 24 of 36
3.
User-friendly interfaces and decentralized applications (apps) that make it simple to
publish, browse, search, review, suggest, curate, verify, and data items, vendors, and
customers will be required for a successful marketplace. People and organizations
should be sufficiently incentivized to build and supply functional and user-friendly
apps while keeping them decentralized.
2.6.1. Cyber Threats or Attacks
The smart economy’s most pressing difficulty is privacy and security concerns. The
smart economy idea, in particular, presents difficulties in analyzing vulnerabilities and
revising strategies. Security concerns are real and must be addressed to guarantee the
sustained achievement of smart city goals. Since security is a costly operation requiring a
large budget, processing in the public sector takes longer. As a result, security and privacy
are essential subjects, particularly in smart economy transactions, which are becoming
more vital for believing the smart city notion of enhancing living standards. As a result,
secure economic services are required to provide quick assistance for transporting data,
mainly via smart city networks. Therefore, it is necessary to have secured financial services
to extend fast support for moving data, especially over smart city networks. The current
research [
3
] aims to briefly present the core concepts of security and privacy issues con-
cerning smart cities and reveal contemporary cyber-attacks targeting smart cities based on
modern literature. Further, this research has elaborated and identified numerous security
weaknesses and privacy challenges about various cyber security issues, challenges, and
recommendations to provide future directions.
This article [
121
] provides a resilient architecture that defends smart city communi-
cations using autonomic computing, and moving target defense (MTD) approaches to
address the most persistent difficulty in the smart economy area. The basic concept behind
attaining robustness is to make it exceedingly difficult for attackers to find out the current
active execution environments utilized to operate smart city services by randomizing the
utilization of these resources at runtime. The authors analyzed and verified their technique
by running a variety of assaults on a smart infrastructure testbed and demonstrating that
the delivered services could withstand these attacks with minimum overhead.
2.6.2. Countermeasures
Under the same assumption, this research [
128
] focuses on the relevance of mobility
and the strength of elliptic curve cryptography in heterogeneous wireless sensor networks
to secure smart city applications. The results of the various simulations revealed that the
proposed dynamic approach to secure smart city applications algorithm improves applica-
tion security by lowering the energy consumption, the number of calculations required, and
the storage space necessary for the elliptic curve cryptography keys. In particular, in the
proposed approach, a powerful mobile cluster head performs operations that demand more
computation and use more battery sensors regularly, such as the development, mainte-
nance, and distribution of elliptic curve cryptography keys and periodic rekeying. Because
the powerful mobile cluster head has no energy limits and is considered impenetrable, it is
a periodic distributor of cryptographic keys to all the data sensors in different applications.
However, the internet-based economy creates several threats, such as unlawful data
copying and digital copyright infringement, posing the problem of preserving the se-
curity and copyright of important data housed in databases. This study [
122
] presents
a unique approach, Lossless Database Watermarking in the Homomorphic Encryption
domain (HOPE-L), to solve this difficulty. The method combines database encryption (ho-
momorphic encryption, order-preserving encryption) and information concealing (lossless
data-based watermarking) technologies. To be more explicit, the information concealing
technique uses the homomorphic encryption algorithm’s features to incorporate hidden
data. Throughout the data-embedding process, no distortion is introduced. As a result, the
proposed approach combines the watermark within the encrypted data without losing any
information. The watermark may validate the copyright, and the receivers can retrieve the
Appl. Sci. 2023,13, 790 25 of 36
original database without losing any data. Theorem and analysis show that HOPE-L can
attain additional embedding space without distortion. Extensive testing demonstrates that
the operating method is time-efficient, the embedded watermark is resilient, and HOPE-L
outperforms previous techniques and can withstand typical database assaults.
In contrast, the creative contribution of blockchain to smart economy activities may en-
hance corporate operations and provide a real-time view of all financial data. On-demand
products, for example, of a signed contract in the shortest period feasible, may considerably
assist financial operations. This process’s approval time is too lengthy, creating an opportu-
nity to use blockchain as a solution. As a consequence of merging the smart economy with
cutting-edge technology, company operations in smart cities may be strengthened by safely
using smart contracts in day-to-day activities. This project [
123
] focuses on the document of
understanding (DOU) contract, which serves as the foundation for the relationship between
a consumer service and the supplier of that service. The authors leveraged local resources
and used design thinking and agile principles to construct a local blockchain ledger for
this assignment. As a result, they produced a proof-of-concept blockchain demo that has
the whole precise history of the agreement, with immutable transactions and transparency,
while providing protection and privacy to the participant’s information. They registered
the time required to obtain the DOU contract signed off by everyone engaged in the process
with this demo, significantly improving it. It may also be reproduced in other areas that
handle sensitive data and financial reporting.
It must be noted that advanced persistent threat (APT) attacks [
129
] are one of the
significant security challenges confronting smart economy sectors in smart cities. APT is a
stealthy threat actor that acquires unauthorized network access and stays undiscovered for
a lengthy period. The targets of these meticulously selected and studied attacks are often
financial institutions or governmental networks. According to this viewpoint, high-level
security requirements must be enforced as smart economy frameworks and infrastructures
grow more technology-dependent. Furthermore, the candidates must work hard in the
front, keeping an eye out for suspicious activity and aberrant conduct. To guarantee
compliance with security rules and regulations, measures are essential to secure the weakest
link in the smart economy IT infrastructure—endpoints and end-user devices.
2.7. Smart People
The smart people’s [
130
,
131
] domain aspires to change how people engage with the
public and commercial sectors as individuals or enterprises via information or service sup-
ply. Increasing social and digital inclusion/equality via educational offerings is necessary
for delivering more efficient communication and services based on new technologies (as
depicted in Figure 7).
Additionally, smart people are about smart types of education that promote job options,
labor market possibilities, vocational training, and lifelong learning for people of all ages
and ethnicities [
132
,
133
]. Talent development is also crucial from an economic development
standpoint since it is becoming an increasingly relevant location element. Smart solutions
for smart people promote the creation of a welcoming and inclusive atmosphere to boost
prosperity and creativity within a city or community. Implementing intelligent solutions
facilitates or fosters participation, open-mindedness, and innovation. In general, a city is
smart because it leverages technology to improve the lives of its residents [1].
Appl. Sci. 2023,13, 790 26 of 36
Appl. Sci. 2023, 12, x FOR PEER REVIEW 27 of 38
Figure 7. Citizen-centric services applications.
Additionally, smart people are about smart types of education that promote job op-
tions, labor market possibilities, vocational training, and lifelong learning for people of all
ages and ethnicities [132,133]. Talent development is also crucial from an economic devel-
opment standpoint since it is becoming an increasingly relevant location element. Smart
solutions for smart people promote the creation of a welcoming and inclusive atmosphere
to boost prosperity and creativity within a city or community. Implementing intelligent
solutions facilitates or fosters participation, open-mindedness, and innovation. In general,
a city is smart because it leverages technology to improve the lives of its residents [1].
Only humans can use technology, improve economic and political efficiency, and
contribute to social, cultural, and urban advancement. However, poor morale and intel-
lect, a lack of qualified human resources, and multi-ethnic conflicts are vital difficulties
that often contribute to societal issues. This study [134] aimed to discover and investigate
the aspects of clever people in a smart city. The research used a mixed-method approach.
Questionnaires, document reviews, and observations were used to gather data. The find-
ings revealed that the variables of agreeableness, conscientiousness, emotional stability,
extraversion, and experience with openness all had high mean scores. Aside from that,
the component of friendliness had the highest average mean score of 3.78 out of the four
factors: conscientiousness, extraversion, emotional stability, and experience with open-
ness. This research indicates that local governments must adopt strategies and policies to
construct and promote smart cities.
2.7.1. Cyber Threats or Attacks
Currently, schools disperse the teaching of various components of data skills
throughout the curriculum. However, as smart city technologies emerge and demonstrate
real promise in contributing to a more sustainable future, it is clear that new skills for
Figure 7. Citizen-centric services applications.
Only humans can use technology, improve economic and political efficiency, and
contribute to social, cultural, and urban advancement. However, poor morale and intellect,
a lack of qualified human resources, and multi-ethnic conflicts are vital difficulties that
often contribute to societal issues. This study [
134
] aimed to discover and investigate the
aspects of clever people in a smart city. The research used a mixed-method approach.
Questionnaires, document reviews, and observations were used to gather data. The find-
ings revealed that the variables of agreeableness, conscientiousness, emotional stability,
extraversion, and experience with openness all had high mean scores. Aside from that, the
component of friendliness had the highest average mean score of 3.78 out of the four factors:
conscientiousness, extraversion, emotional stability, and experience with openness. This
research indicates that local governments must adopt strategies and policies to construct
and promote smart cities.
2.7.1. Cyber Threats or Attacks
Currently, schools disperse the teaching of various components of data skills through-
out the curriculum. However, as smart city technologies emerge and demonstrate real
promise in contributing to a more sustainable future, it is clear that new skills for working
with the large urban data sets that drive these innovations must be taught to future genera-
tions for them to be active smart city citizens. The authors of this study [
135
] question how
data skills might be taught more cohesively and practically, allowing for applying skills
in actual, smart city scenarios. They suggest using urban data games to provide a setting
for learning and showing the practical application of skills for dealing with substantial,
complicated data sets, such as big data on smart home energy use. In this regard, do the
study programs meet the need for smart city education? What are the opportunities for
people to become smart in a smart city? This study [
136
] offers the excellent integration
of smart people educational programs in future smart cities based on practice and a pro-
Appl. Sci. 2023,13, 790 27 of 36
fessional field-oriented, diversity-inclusive approach, as it is commonly acknowledged
that learning by doing may considerably improve students’ understanding of information
security in smart cities. Hands-on laboratories may help individuals learn about security
fundamentals. This study [
137
] includes various hands-on laboratories that might assist
individuals in performing practical exercises in risk-free settings.
However, low motivation is the first barrier when educating end-users about smart
cities. Game-based learning with interactive exercises and engaging multimedia is an
effective way to motivate end-users. Providing a wide range of game material to meet
educational demands is critical. For example, in this paper [
138
], the authors propose a
phishing attack game to describe stereotypical features of phishing attack techniques to
teach people. As anti-phishing games develop as a scalable, motivating, and practical way
for anti-phishing education for non-professional end-users, issues occur owing to a game’s
content and context becoming irrelevant. When a game delivers unfamiliar or unrelated
instances to the user, the learning potential is restricted since the user lacks a reference
point. This study [
139
] presents a customization pipeline for data collecting, creation, and
distribution for anti-phishing learning games to give players more meaningful, relevant
game material. With the rise of remote work and education, it is vital to adopt new
technologies to teach cybersecurity ideas. This work [
140
] describes the concept, design,
and prototype of a mixed reality-based cybersecurity teaching application on phishing
to expose schoolchildren to the topic remotely and allow them to practice distinguishing
harmful from authentic mail.
2.7.2. Countermeasures
On the other hand, there are methods and systems to learn without much input from
humans, e.g., phishing websites can be detected using machine learning by classifying
the websites as legitimate or illegitimate [
141
]. Furthermore, this paper [
142
] describes
a contemporary research group’s attempt to counteract targeted assaults using spear-
phishing by using social engineering via user education (to increase the success probability
of phishing attacks, attackers often adopt social engineering techniques). The authors
specifically establish a link between human psychological features and sensitivity to social
engineering. The outcome may be used to determine if a user has been exposed to a social
engineering approach, and the result can be used for countermeasures or user training.
On the other side, ICT can potentially increase people’s intelligence. This paper [
143
]
describes a system that employs smart plugs, smart cameras, smart power strips, and a
digital assistant such as Amazon Alexa, Google Home, Google Assistant, Apple Siri, or
Microsoft Cortana to capture voice commands spoken in a much more natural manner by a
person with physical disabilities to control ordinary home electrical appliances to turn them
on or off with minimal effort. Moreover, this research [
144
] intends to assist blind persons
using smartphone devices. The program allows users to start any app and call contacts
using voice commands. Speech commands may be used to instruct a mobile device. These
orders are quickly interpreted by the voice recognition engine, which transforms speech
into text for direct actions. This strategy is beneficial when a person feels alone in a low
setting since it allows him to make a voice call to a known individual. Aside from that, the
system offers an app interface that allows the user to obtain the most recent information
from numerous web servers.
To allow smart connections among various devices, smart city technologies have
merged artificial intelligence into smart gadgets. AI-powered smart home gadgets may
interact with one another and collect new data to aid in learning human routines. The in-
formation gathered is utilized to forecast user behavior and establish situational awareness,
i.e., to comprehend user preferences and modify settings appropriately. These values often
clash when recognizing some ideals critical for ethical discussion in AI, such as fairness,
transparency, and accountability. More openness, for example, may result in less privacy.
Introducing higher principles to balance values raises two issues:
Appl. Sci. 2023,13, 790 28 of 36
1.
Principles might contradict one another, deflecting the issue into a purely specula-
tive sphere.
2.
If a higher-level principle is presented and contradicts another, a higher-higher-level
regulation is required to enter an endless regress.
Although AI ethics is part of the so-called field of applied ethics, it appears to be
about applying principles and values and finding the right balance concerning specific
ethical theories, such as Kantian or utilitarianism. Traditional approaches in applied ethics
do not provide sufficient conceptual means to deal with practical problems. As a result,
the difficulties of installing intelligent systems cannot be fully addressed since the same
issue arises: how may values be balanced concerning ethical theories? If higher-level
principles are not feasible for resolving value conflicts, the conditions under which they
may be applied should be considered. Consequently, it is advocated that precise criteria for
implementing the principles be made clear, resulting in at least a clarification for public
discussion regarding some technical developments in AI. Furthermore, it is argued that to
address these conflicts, the implementation must be reviewed to see whether it allows for
future human involvement rather than rendering actions impossible [145].
3. Recommendations
In the face of rising urbanization, city planners are turning to technology to alleviate
many challenges in contemporary cities. Smart cities result from deeper technological
integration into new or existing urban environments. Building a smart city aims to improve
people’s quality of life by leveraging technology to improve service efficiency and meet
residents’ needs. A smart city is a vision for urban development that aims to secure and
integrate multiple information and communication technology solutions to manage a
city’s assets. The smart city is concerned with how the city’s “organism” functions as an
integrated whole and survives in harsh environments. A city’s energy, water, transportation,
public health and safety, and other aspects as critical infrastructure run smoothly while
providing a clean, economic, and safe environment to live and work in [123].
In practice, these transformational impacts will result from the combination of three
components of technology: low-cost logic controllers, millions of sensors attached to
devices scattered around a city, and a network that links all of these nodes and allows
real-time communication. Smart cities rely on networks to ensure the supply and delivery
of functions. Such network connections will allow for more effective and efficient delivery
of urban services. Additionally, these networks aim to present conservation opportunities,
improve efficiencies, and, most importantly, enable coordination among city officials,
infrastructure operators, public safety officials, and the general public [146].
Balancing the promise of smart cities against the potential for cyber risks—and prop-
erly managing the related risks—will be key to fulfilling the smart city potential. To begin,
cities should involve all stakeholders and entities in the greater ecosystem. The following
are the next recommended actions that cities should consider:
1.
Syncing smart city and cyber strategy. Cities should develop a detailed cybersecurity
strategy consistent with their overall smart city strategy and can mitigate issues
coming from the continuous convergence, interoperability, and interconnection of
city technologies. Additionally, they should consider undertaking a thorough impact
assessment of their data, procedures, and cyber assets to identify, assess, and reduce
the risks associated with technical processes, policies, and solutions. Cities may build
a comprehensive cybersecurity strategy with an integrated perspective of the risks
and awareness of the interdependencies of important assets.
2.
Formalizing cyber and data governance. Cities must codify their approach to data
governance, assets, infrastructure, and other technological components. Each impor-
tant part of the smart city ecosystem should have its responsibilities and tasks, which
should be defined in a comprehensive governance model. Multiple entities must
collaborate to apply an ecosystem approach to cyber challenges, with a robust gover-
nance model serving as the foundation. Cities can collaborate with other cities, state
Appl. Sci. 2023,13, 790 29 of 36
agencies, academics, and enterprises to exchange threat information, capabilities, and
contracts to bolster cyber defenses. Furthermore, data management, which includes
rigorous data sharing and privacy policies, data analytics skills, and monetization
models that allow the sourcing and use of “city data,” is an important part of this
governance. Policies, regulations, and technology must be constantly coordinated
to strike the proper balance of protection, privacy, transparency, and utility. The
city’s comprehensive cyber strategy requires the maturation of the government, rules,
and processes.
3.
Build strategic partnerships to grow cyber capabilities [
147
]. Because the cyber skills
gap is not going away anytime soon, cities must be inventive and proactive in filling it
in their communities. Smart cities necessitate the development of new skills and com-
petencies across all ecosystem tiers. Strategic collaborations and contracts with service
providers can help cities supplement their existing skills. His strategy may necessitate
the local administration exploring unorthodox methods of attracting cyber expertise,
such as crowdsourcing, rewards, and challenges to address cyber-related concerns.
Cybersecurity is far too critical to be an afterthought. City leaders must recognize that
protecting cities from cyber risk is not a one-time event in which cyber strategy evolves
as cyber threats grow; rather, it is critical to recovering after a cyberattack occurs. Further-
more, cities cannot or should not fight this struggle alone but rather with an ecosystem
of local governments, academia, the business sector, and entrepreneurs. Technology is
one component of a cybersecurity solution, but it also requires a comprehensive gover-
nance architecture for data and assets. Cities need an integrated strategy for cyber-risk
management, with security concepts baked into every stage of the process.
4. Conclusions
The smart cities paradigm emerges as a reaction to the objective of constructing the
city of the future, where inhabitants’ and industry well-being and rights are secured, and
urban planning is evaluated from an environmental and sustainable standpoint. The
development of smart networks must invariably involve the provision of integrated cyber
and privacy ICT solutions [
65
,
148
]. These solutions must ensure the interoperability of the
various elements that make up the city’s structure and lessen the likelihood that multiple
technologies will become obsolete. The variety of the infrastructures and the dynamism
of their operational environment necessitates a continual reduction in complexity, quicker
processing of expansion works, and the inclusion of equivalent new ones [
3
,
12
]. These
requirements must be met. In addition, unified management proposes clear and definite
ways of providing end-to-end smart services based on robust security standards [
149
] and
ensuring the privacy of the information being exchanged to offer quality services [
150
,
151
].
Smart cities are becoming more interconnected, so this helps.
In this particular piece of work, to assess the developing dangers, some specific events
of threats, attacks, and their respective countermeasures were selected. These are the
kinds of occurrences that have been suggested from time to time in the scientific literature.
The work seeks to be an indicative model that may be considered during the design and
execution of infrastructure improvements connected to smart networks.
Future enhancements will include incorporating operational standards used in in-
dustrial network applications, subject to ongoing modification and reordering, and newly
recognized standards for smart city networks. Additionally, the recording of the general
recommendations by the standardizing bodies per field of operation of the smart networks,
as well as the corresponding gaps that were possibly identified and further concern devel-
opment and evaluation procedures, is a significant development that bears mentioning.
This is another important advancement.
Appl. Sci. 2023,13, 790 30 of 36
Author Contributions:
Conceptualization, V.D., S.D. and K.D.; methodology, V.D., S.D. and K.D.;
software, V.D., S.D. and K.D.; validation, V.D., S.D. and K.D.; formal analysis, V.D., S.D. and K.D.;
investigation, V.D., S.D. and K.D.; resources, V.D., S.D. and K.D.; data curation, V.D., S.D. and K.D.;
writing—original draft preparation, V.D. and S.D.; writing—review and editing, V.D., S.D. and K.D.;
visualization, V.D., S.D. and K.D.; supervision, K.D.; project administration, K.D.; funding acquisition,
V.D., S.D. and K.D. All authors have read and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Not applicable.
Conflicts of Interest: The authors declare no conflict of interest.
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