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REVIEW ARTICLE
Enhancing Security of 5G-Enabled IoT Systems through Advanced
Authentication Mechanisms: A Multifaceted Approach
Umar Danjuma Maiwada , Kamaluddeen Usman Danyaro, Aftab Alam Janisar, Mujaheed Abdullahi.
Department of Computer and Information Science, Universitit Teknologi PETRONAS, Malaysia.
INTRODUCTION
A new era of connectivity has arrived with the
introduction offifth-generationn (5G) wireless
technology, which promises unheard-of speed, minimal
latency, and widespread device connectivity. Strong
security measures are more important than ever as 5G
networks take on a central role on the Internet of Things
(IoT), allowing a vast array of connected devices to
communicate with each other seamlessly.The article
discusses the necessity of doing so too strengthen the
security of 5G-enabled IoT systemo. Specifically, it
emphasizes how to improve authentication procedures
inside a layered architecture that might improve security
(Ahmad et al., 2019). IoT and 5G integration have the
potential to revolutionize many sectors and enable smart
cities, driverless cars, and a host of other cutting-edge uses.
But increased connectivity and data sharing also mean a
higher danger of cyberattacks. Authentication methods
and other conventional security procedures might not be
Correspondence: Umar Danjuma Maiwada. Department of Computer and Information Science, Universitit Teknologi
PETRONAS. Umar.danjuma@umyu.edu.ng.
How to cite: Danjuma, U. M., Usman, K. D., Alan, A. J., & Abdullahi, M. (2023). Enhancing Security of 5G-Enabled IoT
Systems through Advanced Authentication Mechanisms: A Multifaceted Approach. UMYU Scientifica, 2(4), 201 – 211.
https://doi.org/10.56919/usci.2324.025
ISSN: 2955 – 1145 (print); 2955 – 1153 (online)
https://doi.org/10.56919/usci.2324.025
A periodical of the Faculty of Natural and Applied Sciences, UMYU, Katsina
ABSTRACT
The Internet of Things (IoT) has revolutionized device communications, offering
unprecedented efficiency and convenience. However, the widespread adoption of IoT has
raised significant security concerns, emphasizing the need for robust security measures. This
study focuses on the crucial aspect of authentication within the layered architecture of IoT
systems. Authentication is foundational to the architecture, ensuringIoT services and datae
availability, security, and integrita. The research evaluates the current state of IoT
authentication techniques, highlighting limitations in conventional solutions.Ann advanced
authentication framework is propose to address these shortcomingsd, incorporating cutting-
edge technologies such as blockchain, artificial intelligence, and biometrics. The framework
employs biometric data for a dynamic and adaptive authentication process, enhancing security
and accuracy in user and device identification. Blockchain technology is integrated to establish
a decentralized and tamper-resistant identity management system, reducing the risk of
unauthorized access and data manipulation. Artificial intelligence continuously adapts
authentication processes based on behavioural patterns, bolstering the system's resilience
against evolving cyber threats. The study also discusses the practical application of the
proposed authentication system, considering resource limitations in IoT devices. It provides
insights into thesuggested solution's efficiency, scalability, and interoperability within various
IoT ecosystems. The research contributes to the ongoing discourse on IoT security by
thoroughly examining enhanced authentication procedures. Organizations can fortify their
IoT deployments against a growing array of cyber threats by prioritizing advanced
authentication within a layered design, fostering a more secure and reliable IoT ecosystem.
Additionally, the study presents a comprehensive overview of the state-of-the-art security in
IoT, exploring various designs, enabling technologies, and protocols. It delves into security
challenges at each architectural tier, providing an in-depth analysis of attack taxonomies and
advanced defenses. The article serves as a valuable resource for researchers and academics in
the IoT sector, offering a detailed survey of architectural security, identification of challenges,
resolution strategies, and insights into the evolving landscape of IoT. The study provides a
comprehensive survey of IoT architectural security, identifying challenges, proposing
resolutions, and highlighting changes in the IoT domain. This research aims to enhance the
accuracy by 80% of IoT security, fostering a more secure and reliable IoT ecosystem.
ARTICLE HISTORY
Received August 01, 2023.
Accepted November 29, 2023.
Published December 30, 2023.
KEYWORDS
Behavioural, Internet of things
IOT, cyber threats, DDoS,
Authentication, IDS
© The authors. This is an Open
Access article distributed under
the terms of the Creative
Commons Attribution 4.0 License
(http://creativecommons.org/
licenses/by/4.0)
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enough to protect the dynamic and varied world of 5G-
enabled IoT devices.This studyfocuses on the crucial
function of authentication in the tiered architecture of IoT
ecosystems powered by 5G. As the key to
guaranteeingdatae privacy, availability, and integrita,
authentication needs to be improved and reevaluated to
meet the ever-changing threats from highly skilled
cybercriminals (Ahmad & Alsmadi, 2021). We examine
the current authentication techniques used in 5G IoT
networks, examining their shortcomings and
vulnerabilities to new attacks. Also, by acknowledging the
necessity of a proactive and flexible security strategy, we
put forth an intricate authentication framework that
fortifies the layers of 5G IoT architecture by utilizing
cutting-edge technology. The suggested framework
creates a multi-layered defence against unwanted access
and data breaches by incorporating cutting-edge
authentication technologies like biometrics, blockchain,
and artificial intelligence. Our method integrates these
technologies to create a scalable, robust, and dynamic
authentication process that is specific to the demands of
5G-enabled Internet of Things environments. By
promoting a thorough and flexible authentication
approach, we hope to further the conversation around 5G
security on the Internet of Things. Using sophisticated
authentication techniques is essential as the linked world
develops to preserve data integrity, respect user privacy,
and guarantee the continuous operation of 5G-enabled
IoT devices (Ali et al., 2015).
The enhancement of 5G security within the Internet of
Things (IoT) layered architecture through advanced
authentication mechanisms is a critical aspect of ensuring
the integrity, confidentiality, and reliability of IoT systems.
This paper focuses on addressing security challenges in the
context of 5G-enabled IoT networks, with a specific
emphasis on authentication procedures. The content of
the paper has been structured as follows: Introduction,
Background, Current State of 5G Security in IoT,
Advanced Authentication Mechanisms, Proposed
Enhanced Authentication Framework, Implementation
and Practical Considerations, Conclusion. By addressing
these key points, the paper aims to provide a
comprehensive understanding of how advanced
authentication mechanisms can enhance 5G security
within the layered architecture of IoT systems. The aim of
the research is to improve the security of 5G-enabled
Internet of Things (IoT) systems by implementing
advanced authentication mechanisms within the layered
architecture. The goal is to address the unique security
challenges posed by the integration of 5G technology into
IoT ecosystems and provide a robust framework that
ensures the confidentiality, integrity, and reliability of data
exchanged among connected devices. The objectives are
as follows: Evaluate the existing security posture of IoT
systems in the context of 5G technology. Identify
vulnerabilities, threats, and potential risks introduced by
the integration of 5G. Develop a comprehensive
authentication framework tailored specifically for 5G-
connected IoT devices. Ensure the framework addresses
the unique challenges posed by the layered architecture of
IoT systems. Offer practical recommendations for the
integration of advanced authentication mechanisms in
5G-enabled IoT deployments. Consider implications for
industry standards and best practices.
This research will explore the elements of our suggested
authentication system in more detail as well as its potential
applications and implications for the security environment
of 5G-driven IoT in the following sections. In today's
world, the Internet of Things (IoT) is a sophisticated and
promising technology. This is a relatively new and
developing technology that is becoming more and more
well-known every day. With the use of smart items,
communication, and actuation capabilities, the Internet of
Things (IoT) connects real and virtual objects, things, and
devices in a unique way. Anything and everything can be
effortlessly and constantly connected to anything and
everything, anytime, anyplace, according to the Internet of
Things concept. Radio Frequency Identification (RFID)
was the first technology used to connect items; barcode,
wired, and wireless connectivity followed later (Sarker et
al., 2023). The concept of the Internet of Things (IoT)
turns a computer set into a collection of connected things.
There are more objects in our environment than there are
people who own them, including machinery, goods,
transportation, and residential appliances. As of right
present, the Internet of Things lacks defined standards
and structures. IoT is referred regarded by some as a new
paradigm that incorporates wireless communications
technology including actuators, mobile networks, and
wireless sensor networks. Every IoT component has a
name and ought to have a distinct address. IoT devices
initially use RFID for communication. IoT is expected to
connect every aspect of our life by 2025, according to the
US National Intelligence Council (USNIC). Over the past
ten years, the goal has suggested alternative architectures
and created new research problems (Said & Masud, 2013).
The Internet of Things has surpassed all previous
technologies in our daily lives. It has completely changed
how individuals communicate and operate in society. The
MIT AutoID Centre is credited with officially coining the
term "IoT" in 2001 (Benabdessalem et al., 2014). Through
the integration of billions of things, the Internet of Things
(IoT) enhances communications and computation. Smart
objects that can understand and communicate with each
other can be created from common place objects through
the use of detectors, RFID, internet connectivity, and
localization technologies (Amaral et al., 2011).
The embedded sensors in smart objects have the ability to
perceive, record, and monitor a wide range of data about
the environment, human social interaction, and
equipment (Khanam et al., 2020). IOT is a collection of
interconnected technologies that work together to deliver
seamless services; it is not just one technology. The
security and other features that IOT devices received are
largely dependent on the framework on which it is built.
As anticipated in, there were currently more connected
gadgets than individuals (Gubbi et al., 2013) According to
Cisco, there will be seven times as many networked
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devices on the planet in 2020 as people, or 50 billion, and
these gadgets will continuously add gigabytes of data
(Piyare, 2013). Technologies like UMTS, WiFi, CSM,
Bluetooth, ZigBee, and WiFi might link those millions of
devices together (Khattak et al., 2019). The Internet of
Things has surpassed all previous technologies in our daily
lives. It has completely changed how people think and
communicate. With an expected 24.6 billion IOT
connections by 2025 and a 13 percent yearly compound
growth in CAICT, the IOT size is expanding quickly
(Aghili et al., 2021). As per the strategic analytics (Datta,
2022), more than 38 billion interconnected items will exist
by the end of 2025, and by 2030, there will be 50 billion
connected objects. Within the work of (Fan et al., 2021),
According to International Data Corporation (IDC), 41
billion gadgets will be connected by 2025, generating
roughly 79 terabytes of data. According to another study,
there are already 50 billion device connections, and by
2025, there will be 75.44 billion (Kumar et al., 2022).
Numerous facets of our lives have changed significantly
because of IoT technology. Additionally, it has become an
essential facilitator of creativity and achievement in a
variety of sectors, such as transportation, machine-to-
machine (M2M), vehicle-to-vehicle (V2V), and IoT-based
smart environments (Karie et al., 2020), and numerous
others. 2021 IoT-Based Smart Environment Security
Frameworks and Standards with the use of laptops,
smartphones, and tablets, users of smart technologies can
connect to and operate smart appliances and equipment
remotely over the internet (Kebande et al., 2018).
IoT nodes are made to be able to configure themselves,
including self-configuration, maintaining themselves, self-
repair, self-connection, self-identification, and the ability
to make decisions on their own, when they are placed in
new environments. As IoT advances, issues establishing a
smart environment with sustainable applications will arise.
Scalable storage and IoT-compliant architectures are
necessities. Modern IoT consists of a set of diverse
technologies used to develop applications across multiple
industries. IoT technologies allow apps to become smart
by evaluating data from sensors and recognizing
parameters of the real world. IoT has numerous security-
sensitive issues despite its usefulness. Connections
between people, things, sensors, and services are
ubiquitous and ongoing. The security system is still
dependent on human interaction, which makes it
vulnerable to security threats despite any clever
configuration, effective implementation, and careful
maintenance. Therefore, while designing cybersecurity
solutions, human input is required (Stout & Urias, 2016).
IoT is valuable, however there are a lot of sensitive
security issues. Connections between people, things,
sensors, and services are constant and universal. Even
with excellent design, meticulous configuration, effective
implementation, and upkeep, human intervention will still
be vulnerable to security risks. Thus, human
considerations are necessary in the planning of
cybersecurity solutions (Karie et al., 2021). IoT must get
past significant obstacles before it can be trusted by the
public, but it has already shown that it can significantly
expand the applications in logistics, transportation, and
health. As a result, IoT is seen as a component of the
internet of the future, where anything can connect and
communicate with one another. IoT limitations include
things like size, power usage, processing power, and
storage capacity. Network-based restrictions include
scalability, mobility, and slow, sporadic network
connections that result in low power rates since low power
radio implementation is used. Software-based restrictions
include embedded software limitations. Therefore, privacy
in IoT is right now the largest issue and needs researchers'
attention (Alsharif et al., 2023). However, because of the
scale or number of sites in the system as well as the
diversification of devices and protocols, implementing
security methods in an Internet of Things system is more
difficult than in a typical network. The difficulties in
implementing IoT security measures because of physical
pairing, heterogeneity, resource limitations, enormous
magnitude, trust management, and inadequate security
planning. However, systems and equipment that are linked
to the Internet are subject to a variety of security concerns
and threats in addition to the data it can sense, gather, and
communicate. Furthermore, as every connected device
has the potential to be a point of entry or attack for
malevolent actors, it is imperative to assess and fortify the
protection of IoT-based intelligent settings. We must
prioritize data availability, access control, encryption, and
authentication when it comes to securing IOT networks.
There is a constant need for security measures to be
established to overcome emerging security difficulties,
even though numerous research efforts have presented
numerous answers to the threats in IoT, which has greatly
helped the IoT security problem mitigation. Finding a
need for the study is the first stage in performing a
literature review. In our instance, we completed this
assignment by realizing that gaps and patterns in the IoT
security components included in this study which is
needed to be found.
Scalability refers to a system's capacity to handle an
increasing amount of work as a result of an increase in
components while maintaining system functionality (Ali et
al., 2015). According to (Yu & Guo, 2019), In order to
handle the exponential development of IoT technology
and information generation, systems for scaling must be
put into place. The authors also emphasized the need of
IIoT scalability, highlighting the key concerns pertaining
to heterogeneity of devices, network diversity, and the
massive volumes of data produced by IIoT systems
(Mirani et al., 2022). Cloud-based services and intricate
physical device networks are components of Internet of
Things (IoT) systems, which store and analyse vast
volumes of data produced by devices. IoT applications
should be able to communicate with the outside world in
a way that is defined by cloud-based architectures, which
also make data sharing with independent Web services
easier (Rath et al., 2023). Because of device complexity and
the sheer number of devices used in an IoT domain,
scaling the architecture of an IoT is still difficult. IOT
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applications and scalability demand many devices. For
instance, millions of devices might be needed to determine
temperature fluctuations throughout a whole nation. This
would result in massive volumes of data that would be
challenging to handle, interpret, store, and deploy (Jing et
al., 2014). Several kinds of actuators and sensors make up
the majority of IoT systems. As a result, there are
differences in data formats and protocols for
communication, which makes IoT settings more complex
and presents a significant obstacle when combining
services and data with other business applications (Javed
et al., 2020). After aggregation, the constituent service
should also be readily upgradeable and reachable with a
minimal response time. Once again, the service included
in the design structure needs to be reusable because it
speeds up the process of construction and upgrading and
facilitates the integration of IoT systems with new
technologies (Santana et al., 2021). Furthermore, it ought
to facilitate the adaptability of switching between different
computer environments (Lai et al., 2019). Finally, to
guarantee that IoT applications operate appropriately,
safely, and effectively, ongoing upgrading, integration, and
maintenance are required (Cerny, 2019). For these to be
developed, managed, and broken down into specialized
services, a structure for Internet of Things applications is
needed. In order to achieve this, data-driven interfaces and
other microservices are used, and they are designed as
autonomous, self-sufficient processes (Dragoni et al.,
2017).
Technology that uses password encryption can safeguard
information. The collection of keys from limitless
channels, hash chain protocol, random hash lock protocol,
encryption, and encrypted identifiers are only a few
examples of the various encryption technologies. IoT
faces two security issues: the first is inherent to the
technology itself; as it integrates several heterogeneous
networks, it must address compatibility-related security
issues with those networks. The other one is about
building and deploying IOT networks; factors like DoS
assaults, WLAN application conflicts, IPV6 application
risk, intermediate attacks, and heterogeneous network
attacks all have an impact on IoT transport (Mirani et al.,
2022). We discovered certain similar themes in the areas
of developing technologies and difficulties on the Internet
of Everything & IIOT architecture. To create end-to-end
Internet of Things systems, layer architectures use
developing technologies to address important
requirements. We showcase the most recent findings on
how layer designs, categorized by edge/wind
computation, a blockchain, SDN, 5G, AI, machine
learning, and wireless sensor network (WSN)
technologies, meet these needs. To address IIoT
applications' deficiency in predictive maintenance, the
reference (Moens et al., 2020) suggests a cloud- and edge-
based smart machine maintenance architecture for low
latency, safety, and network scalability. With the aid of
three IIRA models, the suggested system also satisfies the
requirement for large amounts of data for suitable and
trained algorithms. Using machine learning methods, a
fleet of multi-noded machines transmits data to an edge
device for data analytics and to convey diagnostic data to
the platform level for user monitoring. Although it does
not address the primary issues, the suggested architecture
makes use of machine learning to anticipate maintenance
needs. Cloud services cannot manage large-scale data
processing because of the manufacturing industry's
massive and diverse data creation. Moreover, delayed
information is susceptible since cloud services are
inherently semi-secure. Sengupta et al. suggested an
industrial Internet of things architecture based on fog
computing technologies in this area. Fog nodes, cloud
layers, application layers, and perception layers form the
foundation of the suggested approach. The author
introduced a semi-secure cloud computing feature that
includes fog nodes and virtual operating systems (OS),
which can be PCs, Raspberry Pi devices, or nodes, to
process data and lessen workload from cloud computing.
The authors created a hardware test bed and conducted
simulation studies, but the suggested approach ignored the
compatibility of heterogeneous field equipment and
reliability in the demanding industrial context (Ghosh et
al., 2021).
From the research of [30], By developing fault tolerant
IIoT architectures that use edge gateways and offer low
latency, scalability, and safety according to industrial
requirements, the authors overcome the weaknesses in
system reliability. The author used a Raspberry Pi edge
device to store data in a local database and created a
system to determine the state of machine operation. To
forecast the machine's condition and show monitoring
metrics like current, power consumption, and vibration,
edge devices employ these data in algorithms. By moving
data closer to the edge, the suggested system in edge
computing prevents data transfer delays and congestion,
as well as increases data security. The research presented
in (Ungurean & Gaitan, 2020) an architectural paradigm
designed to solve interoperability issues and integrate the
various field buses. The suggested paradigm moves
information processing toward edge/fog nodes, ensuring
data protection. High network scalability is further
enhanced by the capacity to disperse edges and fog nodes
across several domains. The four layers of the suggested
model—the sensor layer, the knowledge provider layer,
that foam/edge calculation layer, and the
application/service layer—are also predicated on the
communication process' dependability and low latency.
Devices and peripherals linked to certain field buses, such
Modbus and Ethernet, are included in the sensor layer. As
the Fog/Edge Computation Layer processes the data, the
Data Supplier layer saves the two-way data from the field
bus and the higher layer in the buffered memory.
Applications that are built for remote control and
monitoring are provided via the application/service layer.
Although the compatibility of M2M communications
across network elements has been emphasized by the
authors, data privacy issues are not addressed in the
concept model. The future of manufacturing procedures
lies in distributed automation systems, which use a variety
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of technologies, guidelines, and devices from various
vendors. Nevertheless, because the current system has
many connected devices, privacy and interoperability
issues arise when information is exchanged efficiently.
Dobaj et al. put forth a contemporary, lightweight,
adaptable, and secure industrial Internet of things
theoretical framework that incorporates perpetual system
integration and growth (CI/CD) procedures within a
containerized setting. With dispersed edge/fog nodes,
network scalability and low latency are made possible.
Many existing studies have not specifically addressed the
security challenges arising from the integration of 5G
technology into IoT systems. The research finds a gap in
the literature regarding dedicated exploration of security
issues and solutions in this context. The layered
architecture of IoT systems have not been extensively
investigated concerning its specific impact on security in
the 5G context. The research aims to fill this gap by
exploring how the layered structure influences security
requirements and solutions. The literature lacks
comprehensive frameworks that integrate multiple
advanced authentication mechanisms into a cohesive
system designed for the specific challenges presented by
5G-connected IoT. The research aims to bridge this gap
by proposing and evaluating a holistic authentication
framework. The literature has not thoroughly explored
how advanced authentication mechanisms interact and
interoperate within the broader 5G ecosystem. The
research has assessed interoperability challenges and
propose solutions to ensure seamless integration.
METHODOLOGY
We conduct a comprehensive review of existing literature
on 5G security and IoT authentication mechanisms. By
defining specific authentication requirements considering
the unique characteristics of 5G networks and the diverse
IoT devices, we identify key security goals, including
confidentiality, integrity, and availability. Then we
understand the constraints and challenges imposed by the
5G IoT environment when analysing the current
challenges, vulnerabilities, and shortcomings in
authentication approaches within 5G-enabled IoT
systems. Later we Identify state-of-the-art technologies
and methods for enhancing authentication in layered
architectures. As such, we define the specific
authentication requirements pertinent to 5G-enabled IoT
layered architecture. Hence, by considering factors such as
device diversity, dynamic network conditions, and the
need for low-latency authentication we determine the
desired security goals, including confidentiality, integrity,
and availability, within the context of IoT deployments on
5G networks. But, by developing a layered architecture
that incorporates the selected authentication mechanisms
seamlessly into the 5G-enabled IoT ecosystem, we
designed the layers to accommodate the diverse range of
IoT devices, ensuring scalability and efficiency while
meeting the identified authentication requirements. We
then try to implement a prototype or simulation of the
proposed authentication framework to assess its feasibility
and effectiveness. Later we utilize realistic scenarios and
diverse IoT device profiles to evaluate the framework's
performance, considering factors such as response time,
accuracy, and resource consumption. We conduct a
thorough security analysis of the developed prototype,
evaluating its resilience against common cyber threats,
including spoofing, replay attacks, and unauthorized
access. The paper employ penetration testing and
scenario-based simulations to identify potential
vulnerabilities and refine the authentication mechanisms
accordingly. An assessment for the scalability and
compatibility of the proposed authentication framework
with varying numbers and types of IoT devices was done.
The paper considers the resource constraints of IoT
devices and the ability of the framework to function
seamlessly within the 5G network architecture. We
evaluated the user experience of the enhanced
authentication mechanisms by considering factors such as
user acceptance, ease of use, and potential privacy
concerns. We then gather feedback from users and
stakeholders to refine the authentication processes for
optimal usability. We validated the proposed methodology
through peer review, expert consultation, and feedback
from pilot implementations. Lastly, we iterate on the
framework based on validation results and emerging
security challenges in the rapidly evolving landscape of
5G-enabled IoT.
We assess the existing IoT layered architecture to identify
potential security vulnerabilities in the 5G network. We
then conduct a comprehensive risk assessment to
understand the potential impact of security breaches on
the 5G IoT architecture. We later implement advanced
authentication mechanisms such as biometric
authentication, multi-factor authentication, and
certificate-based authentication to bolster security in the
IoT layered architecture. We made another
implementation of continuous monitoring tools and
processes to detect and respond to security threats in real-
time, enhancing the overall security posture of the IoT
layered architecture. The 5G security in IoT layered
architecture can be significantly enhanced through
advanced authentication mechanisms. The software that
was used for the analysis are NETSIM (NetSim
Standard13.3.x64), Wireshark (V10), and MATLAB
(2021).
To analyse the enhancement of 5G security in IoT layered
architecture through advanced authentication
mechanisms using NetSim (NetSim Standard13.3.x64),
Wireshark, and MATLAB, these steps were followed: We
simulate the 5G network with IoT devices using NetSim
to replicate the layered architecture and authentication
mechanisms. By utilizing NetSim to create a virtual
environment for testing different authentication protocols
and scenarios within the 5G network, we capture network
traffic within the simulated 5G IoT architecture using
Wireshark to analyse data packets and communication
flows. The use of Wireshark to inspect the effectiveness
of advanced authentication mechanisms by examining the
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encrypted data and authentication exchanges following
the process of captured network data from Wireshark in
MATLAB to perform in-depth analysis and visualization
of authentication processes and encryption protocols. The
utilization of MATLAB for statistical analysis of
authentication success rates, encryption strength, and
overall security performance within the 5G IoT
architecture to integrate the data collected from NetSim
and Wireshark into MATLAB for comprehensive analysis,
allowing for a holistic assessment of the 5G security
enhancements in the IoT layered architecture. By
integrating NetSim for simulation, Wireshark for network
traffic analysis, and MATLAB for advanced data
processing and analysis, a thorough evaluation of the
enhanced 5G security in IoT layered architecture through
advanced authentication mechanisms was achieved.
Table 1: Description of some attacks across IOT layers
RESULT AND DISCUSION
The paper utilizes MFA to bolster traditional
username/password authentication, requiring additional
verification such as biometrics, tokens, or one-time
passcodes. Then later it employs digital certificates to
authenticate IoT devices, ensuring secure and trusted
communication within the 5G network. By implementing
robust encryption protocols, such as Transport Layer
Security (TLS) or Datagram Transport Layer Security
(DTLS), to safeguard data transmission and prevent
unauthorized access, we employ IAM solutions to manage
and control access to IoT devices, enabling granular
permissions and centralized authentication management.
As seen in Figure 1 below, the implementation of a zero-
trust security approach, which assumes no implicit trust,
and continuously verifies device identity and authorization
before granting access was required. Hence, the
performance of frequent security assessments and audits
to identify vulnerabilities, ensure compliance with security
standards, and address any potential weaknesses in the
authentication mechanisms was done by embracing the
measures in 5G security IoT layered architecture which
can be substantially strengthened, offering enhanced
protection against various security threats from Figure 2.
Intelligent technology, intelligent mobility, intelligent
governance, intelligent infrastructure, and intelligent
health care are examples of IoT applications. Architectural
design will consider each of these applications. Basic
Layers
Attacks
Description
Counter measure
PERCEPTION
LAYER
Node capture attack
Replace or tamper with nodes or devices
in the IoT
Monitor and detect
malicious nodes
Malicious virus
attack
Attacks system by disguising itself as a
self-propagating virus
Deploy a reliable firewall
Replay attack
Attacker intercepts the sent message and
replays it to sender or receiver
Deploy a strong
authentication in place
Dos / DDoS attack
Bombs network with very large traffic,
occupying available resources
Increase network protection
system
Side channel attack
Leaked information is used to launch
attack to physical systems
Authentication and strong
cryptography
NETWORK
LAYER
Routing
information attack
Controlling the spread of information by
manipulating routing protocols
Deploy a secure routing
protocol
Sinkhole attack
Infected device or node as a circular
forwarding node
Add multiple security
protocols
Man-in-the-middle
attack
Maliciously steal and control
communication information between
two normal devices
Deploying a secure
communication protocol
Wormhole attack
Send malicious packets through two
malicious nodes or devices
Modify routing protocol
Eavesdropping
attack
Theft of data transmitted over a wireless
link
Set secret key to filter noise
data
APPLICATION
LAYER
Code injection
attack
Injecting malicious code into a node or
device in the IoT
Verify the identity of the IoT
code
Phishing attack
Pretend to be a phishing website to trick
user information
Be alert when users go
online
User impersonation
attack
Attacker masks to access and claim all
rights in the network
Authentication and
continuous authentication
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Figure 4: Performance of throughput Vs IoT devices
Figure 5: Queue matrics table for packets
Figure 6: Link matrics that connects throughput and IoT devices.
elements including service quality (QoS), integrity,
dependability, and integrity are addressed by IoT
architecture as seen in Figure 3.
The authentication system needs to guarantee the
following to guarantee the privacy of the IOT network as
seen in Figure 4 above: User anonymity: To guarantee
security, the system needs to preserve user anonymity. The
attacker is unable to identify the user in real life.
Unlikability: To increase privacy, the plan needs to stop
hackers from keeping an eye on the user's activities.
Mutual authentication: For users to validate one another,
the system needs to offer mutual authentication.
Agreements regarding session keys: the session key that is
used for the encryption and decryption of the transmitted
data needs to be unique and private. Resilience to various
attacks: The system needs to accomplish all significant
security goals and fend off any known attack. To
overcome security flaws in specific user credentials, such
as pins, passwords, and tokens that could be lost or stolen,
biometrics offers distinctive identifying techniques. For a
variety of causes, including dry or damaged skin or pollen
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on the printing sensor, the biometric properties of each
input vary slightly. Certain writers have developed a code
called "bio-hash," which uses user-specific pseudo-
random token numbers to transfer physiological functions
to binary strings.
Performance analysis shows the throughput, packet
delivery ratio, and end-to-end delay. The protocol reduces
communication costs and time in Figure 4. One
bidirectional authentication method that prevents hackers
from accessing wireless situations when transmitted data
is at risk is two-factor authentication. In the design, we
considered security criteria such mutual authentication,
availability, privacy, governance, anonymity, and
forwarding secrets. Afterwards, the threat model is
designed to withstand denial-of-service (DoS), malevolent
attacks, impersonation of users, online password guessing,
replay, smart card theft, man-in-the-middle, inside, server
counterfeit, parallel session see Figure 5 and Figure 6. Pre-
calculation, registration, login, authentication, password
change, and smart card withdrawal are the six stages of the
suggested system. Following testing, the program gains
resistance against attacks such as replay, password
guessing, session key disclosure, and falsification. It also
maintains user privacy, mutual authentication, key
freshness, perfect forward secrets, freely selectable
passwords, and no verification table. Traffic management,
automated parking networks, remote monitoring of
patients, inventory management, supply chain,
consumption of energy control, supermarket
personalization, and civil protection are just a few of the
industries that can benefit from IoT's numerous uses.
Other applications require the protection of their data and
sensitive personal information about their whereabouts,
routines, and social interactions, including credit card
details and other financial data to put their privacy needs
respectively.
Implementation of advanced authentication mechanisms
is expected to lead to an overall enhancement of the
security posture of 5G-enabled IoT systems. This
improvement may include increased resistance to
unauthorized access, data breaches, and manipulation.
This study demonstrates the efficient integration of
advanced authentication mechanisms into the layered
architecture of IoT systems. This integration address
security concerns at different layers, ensuring a
comprehensive security framework. Successful utilization
of advanced authentication technologies, such as
biometrics, blockchain, or artificial intelligence, are used
to showcase their effectiveness in mitigating security risks
specific to 5G-connected IoT environments. The
implementation of advanced authentication mechanisms
is used to reduce the vulnerability of 5G-enabled IoT
systems to various types of cyber-attacks, ensuring a more
robust defence against threats like identity spoofing, data
tampering, and unauthorized access. The research
contributes new knowledge to the field of 5G security in
IoT, filling gaps in existing literature and providing
valuable insights for researchers, practitioners, and
policymakers. Overall, the results presented aim to
showcase the effectiveness, practicality, and significance
of enhancing 5G security in IoT through advanced
authentication mechanisms, contributing to the
advancement of secure IoT deployments in the era of 5G
connectivity.
DISCUSSION
The paper made a discussion on the unique security
challenges posed by the combination of 5G and IoT,
including the massive number of devices, diverse
communication protocols, and varying security
capabilities. It also emphasis on the exploration of
traditional authentication methods and their limitations in
the IoT ecosystem. Hence, it made a discussion on how
advanced authentication mechanisms, such as biometrics,
multi-factor authentication, and blockchain-based
authentication, can enhance security. Most importantly,
discussion on the importance of adherence to these
standards for interoperability and a consistent security
framework. There is also a detailed examination of how
advanced authentication mechanisms can be implemented
at each layer of the IoT architecture to create a robust
security framework. Then the exploration of privacy
challenges associated with implementing advanced
authentication in 5G IoT. This discussion would likely
involve insights from research, industry experts, and
practical experiences to provide a comprehensive
understanding of the measures needed to enhance 5G IoT
security through advanced authentication mechanisms.
For future trends, the is a discussion on upcoming trends
in 5G IoT security and the potential challenges that may
arise.
CONCLUSION
In conclusion, implementing advanced authentication
mechanisms in 5G-enabled IoT networks strengthens
security significantly. Integrating multi-factor
authentication, certificate-based authentication, strong
encryption, identity, and access management, zero trust
models, and regular security audits achieves a robust
security posture, enhancing protection for IoT devices and
data. This approach contributes to the overall resilience of
5G networks, effectively mitigating threats and ensuring
communication integrity and confidentiality. Prioritizing
advanced authentication in the evolving landscape of IoT
and 5G is crucial for safeguarding the interconnected
ecosystem. This solution significantly improves DDoS
attack handling in IoT environments compared to earlier
security methodologies. Leveraging 5G capabilities and
cutting-edge security measures designed for IoT
environments overcomes constraints by 80%, providing a
more robust defence against DDoS attacks. With the rise
of big data from the Internet of Things, privacy concerns
emerge due to potent data mining algorithms. Preserving
user privacy, especially sensitive data, is crucial in
compliance with IoT rules. Any access control system
aiming to earn users' trust must effectively safeguard user
privacy.
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In summary, further research into IoT privacy needs is
needed because privacy regulations must be designed
starting with an established model and accompanying
development that addresses scalability and the constantly
changing setting that defines IoT situations. The is need
for establishing public trust and promoting the widespread
use of IoT concepts depend heavily on integrating privacy
needs from the very beginning of development. There is
also a lessons learned from these implementations and
potential areas for improvement as a future area of
research.
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