Industry 4.0 Solutions Impacts on Critical Infrastructure Safety and Protection–A Systematic Literature Review

Abstract

In today's turbulent and complex times, the importance of the functional security and continuity of critical infrastructure (CI) is of particular importance. The Industry 4.0 (I4.0) toolset contains many technologies that support CI or are an integral part thereof. The purpose of this paper is to examine the relationship between CI and I4.0. The goal will be achieved by (1) conducting a systematic literature review using VOSviewer, (2) identifying leading research topics using Latent Dirichlet Allocation, (3) mapping the results obtained and identifying possibilities for further research. Web of Science, Scopus, and a set of specific keywords were used to select peer-reviewed papers presenting evidence of the considered connections. Selected clusters and topics were used to build a reference framework formed by relations between CI and I4.0. The results revealed that despite the popularity of both issues, studies examining the mutual relations between the same are lacking. The added value of the article is that it organizes the knowledge related to relations between I4.0 and CI, and indicates the research areas that require further scrutiny. It is the first comprehensive literature review focusing specifically on CI & I4.0.

Full text

Received 5 July 2022, accepted 26 July 2022, date of publication 1 August 2022, date of current version 10 August 2022.
Digital Object Identifier 10.1109/ACCESS.2022.3195337
Industry 4.0 Solutions Impacts on
Critical Infrastructure Safety and
Protection—A Systematic
Literature Review
MICHAL WISNIEWSKI 1, BARTLOMIEJ GLADYSZ 2, KRZYSZTOF EJSMONT 2,
ANDRZEJ WODECKI 1, AND TIM VAN ERP 3
1Faculty of Management, Warsaw University of Technology, 02-524 Warsaw, Poland
2Faculty of Mechanical and Industrial Engineering, Warsaw University of Technology, 02-524 Warsaw, Poland
3University of Southern Denmark, 5230 Odense, Denmark
Corresponding author: Michal Wisniewski (michal.wisniewski@pw.edu.pl)
ABSTRACT In today’s turbulent and complex times, the importance of the functional security and continuity
of critical infrastructure (CI) is of particular importance. The Industry 4.0 (I4.0) toolset contains many
technologies that support CI or are an integral part thereof. The purpose of this paper is to examine the
relationship between CI and I4.0. The goal will be achieved by (1) conducting a systematic literature review
using VOSviewer, (2) identifying leading research topics using Latent Dirichlet Allocation, (3) mapping
the results obtained and identifying possibilities for further research. Web of Science, Scopus, and a set
of specific keywords were used to select peer-reviewed papers presenting evidence of the considered
connections. Selected clusters and topics were used to build a reference framework formed by relations
between CI and I4.0. The results revealed that despite the popularity of both issues, studies examining
the mutual relations between the same are lacking. The added value of the article is that it organizes the
knowledge related to relations between I4.0 and CI, and indicates the research areas that require further
scrutiny. It is the first comprehensive literature review focusing specifically on CI & I4.0.
INDEX TERMS Bibliometrics, critical infrastructure, Industry 4.0, literature review, reference framework,
smart manufacturing.
I. INTRODUCTION
A. INDUSTRY 4.0 BACKGROUND
Industry 4.0 (I4.0) was first introduced in 2011 as a strate-
gic initiative of the German government [1], [2]. Many
modern economies launched similar initiatives, e.g. US’
Advanced Manufacturing Partnership’, Chinese ’Made in
China’, British’ Smart Factory’, Japanese’ Super Smart Soci-
ety’, and others [3]. Majstorovic and Mitrovic listed almost
40 national programs under the category of I4.0 [4].
The purpose of the paper is to show the spectrum
of I4.0-related topics covered in the in the available
The associate editor coordinating the review of this manuscript and
approving it for publication was Francisco Perez-Pinal .
literature, especially in the context of links to critical
infrastructure. The authors intentionally do not limit them-
selves to the main currents related to I4.0 by presenting
the results of analysis of data available in bibliometric
databases.
The idea of I4.0 is to transition from centralized production
towards greater flexibility and self-control. This direction nat-
urally follows from the historical developments in computer
integrated manufacturing (CIM) and flexible manufacturing
systems (FMS) [5] made in past decades, as well as the
mass digitization observed in recent years [6]–[8]. I4.0 is a
network approach that complements CIM through ICT [9].
It is worth mentioning that the development of the toolset
of I4.0 solutions and technologies has benefited not only the
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M. Wisniewski et al.: Industry 4.0 Solutions Impacts on CI Safety and Protection
manufacturing sector but also the service sector (e.g. big data
solutions in banking or marketing).
With the current advanced technologies, the ideas of CIM
and FMS could be implemented at significantly lower (more
rational) costs. I4.0 is technology-driven and its toolset
covers technologies and solutions such as flexible automa-
tion, cyber-physical systems (CPSs), industrial Internet of
Things (IIoT), embedded sensors, collaborative and cognitive
robotics, cloud and edge computing, big data, computer mod-
eling and simulations, additive manufacturing (3D printing),
artificial intelligence, or the industrial Digital Twin [10]–[14].
Substantial benefits are expected from I4.0 technologies
and solutions, e.g., more accurate forecasting and plan-
ning, shorter lead times, an increase of energy efficiency,
decrease of waste, workplace improvements (an increase
of ergonomics and occupational health and safety), etc.
However, relatively early phases of the I4.0 technologies’
lifecycle imply serious questions and concerns regarding,
e.g. the related social threats, economic effectiveness, or envi-
ronmental impact. These can prove cost-intensive and lead
to difficulties estimating the actual financial benefits and
economic effectiveness, as well as problems related to
increased electro-waste, energy consumption, the incidence
of human-robot interaction issues, technophobia, unemploy-
ment threats, or privacy issues to name just a few [15].
An additional problem is the issue of security, which may
be defined differently by each entity. Safety involves a wide
range of things, systems, and processes. The security issues
could be categorized into three levels, namely, the process
level, the data level, and the infrastructure level. Manufactur-
ing companies may define the security of their operations as
the continuity of their own processes, for example. Service
enterprises operating in cyberspace will define security as:
availability, integrity and confidentiality of processed data.
CI operators, on the other hand, will focus on the security
of managed infrastructure in the context of: cyber security,
physical security, technical security, legal security, personal
security and business continuity. The accepted understand-
ing of the concept of security determines the set of actions
implemented with the intention of protecting the enterprise’s
operations.
Commonly labelled as the ABCD (i.e., artificial intelli-
gence, blockchain, cloud computing, big data analytics) tech-
nologies are essential in enhancing the safety and security
of I4.0 systems. However, the digital twin (DT) also plays
an important role. DT could be depicted as the successor
of the computer simulation approach. It could be used to
support the design and flexible reconfiguration of the system.
DT enables quick validation and tests to locate the malfunc-
tion and inefficiency reasons, rule out the mistakes, and test
the practicability and safety/security of physical solutions in
a cyber environment [16]–[18].
The Internet of Things (IoT) facilitates the integration of
automation technologies under this approach within the pro-
duction environment [10]. This allows the assets of an entire
factory to become interconnected, creating an intelligent
network. I4.0 applications also impact systems reliability
affecting the same in two distinct ways. On the one hand,
they increase reliability by providing new functionalities (like
forecasting, planning, real-time data acquisition, etc.). On the
other hand, I4.0 technologies facilitate new subsystems and
maintenance that need integration with each other and the
existing environment [19].
In this paper, the authors focused on safety, which involves
many things, systems, and processes. Instead of more narrow
and technical security issues, that could be categorized into
three levels (process, data, infrastructure). Many studies high-
light options to apply different technologies to I4.0 solutions
and systems to enhance systems’ security, transparency, and
traceability.
Special attention is currently put to blockchain solutions
and their abilities to obtain:
- sustainable manufacturing and lifecycle [20]–[22],
- secure digital twin technology (off-chain and on-chain
merger) [23],
- anti-counterfeiting of things in the industrial internet.
Some current studies focus not only on physical signatures,
e.g. optical technologies like QR codes, radio technologies
like UHF RFID or NFC, among others, but also on biological
features or edible chemical signatures for things counterfeit-
ing in an I4.0 context [24], [25]. Blockchain security is an
issue itself as well [26]. The picture shows that some areas
like blockchain are discussed in detail on many levels. How-
ever, those studies are focused on technical issues. They miss
the broader business context of critical infrastructure, where
efficacy is over effectiveness. They also ignore the broader
context of the holistic environment that is the I4.0 system and
focus purely on security aspects, leaving more complex safety
issues not covered.
Therefore, I4.0 is dependent on the efficacy of the infras-
tructure providing access to energy, water, communications,
transport, and ICT networks. A part of this infrastructure is
referred to as Critical Infrastructure (CI).
B. CRITICAL INFRASTRUCTURE BACKGROUND
The term ‘‘critical infrastructure’’ was first coined by presi-
dent Bill Clinton’s 1996 Commission on Critical Infrastruc-
ture Protection, and the concept received additional attention
after the 9/11 attacks in 2001 [27]. It is centered on the
notion that CI is of essential importance for economic secu-
rity, national defense, and the public. However, there is no
global consensus as to which systems should be considered
as elements of CI. The specific identification of CI depends
on the preference of the state in question. However, systems
such as electrical power, transportation, healthcare, gas and
oil, telecommunications, transportation, banking and finance,
emergency services, continuity of government, and water
supply are commonly included [28], [29].
Regardless of the definition, CI components are subjected
to different types of threats due to the behavior of individuals,
natural disasters, military operations, terrorism, or cyber-
crime. The efficacy of CI, measured by the availability of
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M. Wisniewski et al.: Industry 4.0 Solutions Impacts on CI Safety and Protection
its functionality, determines the citizens’ perception of safety,
rate of economic growth, social satisfaction, the sovereignty
of the state, and effectiveness of public administration enti-
ties. Limited functionality of CI results in economic losses,
environmental pollution, and a threat to the population’s
health and life [30].
Research pertaining to CI can be divided into two cate-
gories. The first focuses on particular critical infrastructures
and their respective issues on a case by case basis, and
the second on analyzing and governing critical infrastruc-
tures from a cross-sector perspective. The reviewed literature
shows an evident limitation concerning the type of the infras-
tructure sectors analyzed. CI sectors such as finance, health-
care, food supply, public administration, safety and security,
social insurance, and trade and industry are not considered
or, in several cases, only included in combination with other
sectors. Instead, there is a clear focus on sectors such as
transportation, energy, water and sanitation, and information
and communications. Many research initiatives have recently
been carried out in terms of:
- the overall strategies of CI management or
protection [31], [32],
- using CI as variables when estimating the vulnerability
of various areas to flooding [33], [34],
- the impact of CI on national security in the domains of
economic development, state sovereignty, and improve-
ment of the overall standard of living [35], [36],
- the mutual interactions between CI systems [37], [38],
- dependent risk [39], [40],
- methods from the domain of management science which
can be adapted to the management of CI safety [41],
- methods of exchanging information on threats to which
CI facilities are vulnerable [42], [43],
- establishing a safety threshold for the functionality of CI
facilities [44], [45].
C. INDUSTRY 4.0 ROLES IN CRITICAL INFRASTRUCTURE
Some I4.0 technologies will soon become or are already
becoming integral parts of CI, e.g.
- Several manufacturing and service sectors widely con-
sider the use of big data, blockchain, and edge comput-
ing technologies [46], [47];
- Cybersecurity is rapidly developing and the readiness
to fend off large-scale attacks on critical infrastructure
has improved dramatically [48], e.g. in the energy sector
in the Gulf Cooperation Countries [49], manufacturing
sector [50];
- Artificial intelligence supports CI systems [51], [52];
- Industrial automation [53], robotics [54], sensors,
CPS [55], [56], IIoT [57], digital twins [58] enrich deci-
sion makers with data and enable extensive preventive
and resilience capacities in CI;
- Parts manufactured using additive manufacturing can
enhance the technical resilience of CI [59], but also
create new potential targets for attacks (physical and
cybernetic) within safety-critical infrastructure.
Consequently, I4.0 is dependent on CI but at the same time
also shapes the same through technological applications [60].
CI systems provide the basis for utilizing I4.0 technologies,
and thus impact overall economic, environmental, and social
sustainability. The complexity of the relationship between
sustainability, I4.0, and CI requires a holistic approach to the
management of CI safety, understood as maintaining business
continuity. However, the progress of research done in areas
relevant to CI varies. Studies cover only excerpts related
to the CI safety management process. There is a lack of a
proposal for a holistic solution to CI safety management.
Therefore, said safety becomes dependent on I4.0 solutions,
which means that apart from the efficacy paradigm, it should
also be considered from a sustainability perspective.
I4.0 is also discussed in terms of its impact on national
security [44]. Some systems and solutions combine recently
emerging new technologies, e.g., cyber-physical systems,
but no single technology is likely to solve a problem with-
out being integrated with other technologies. Combined, all
such technologies might find applications in in CI systems.
Therefore, I4.0 could deliver benefits in terms of better CI
management, increased CI protection, etc. At the same time,
however, when I4.0 solutions become integral parts of CI
systems, they become additional sources of potential risk as
the respective subsystems must be considered in terms of their
safety and security [45] (especially occupational health [46],
cybersecurity [47]), and reliability [48], etc.).
Considering the rapidly increasing popularity of I4.0 solu-
tions, their increasingly important role in industrial sys-
tems, and the importance of CI security for businesses
and economies, the goal of the present study is to deduce
their relations and interactions by analyzing the existing
body of scientific peer-reviewed literature. In this paper,
a literature-based analysis is performed to determine the
relationship between I4.0 and CI across different industries.
CI and I4.0 relations are still quite fuzzy. The analytical
approach proposed below entails a comprehensive qualitative
assessment based on a literature review and bibliometrics.
Therefore, the paper is focused on a systematic literature
network analysis with a view to identifying connections
between I4.0 and CI by analyzing the citation network,
co-occurrence of keywords network, and Latent Dirichlet
Allocation approaches. The review presented below is ori-
ented towards investigating the mutual relationship between
CI and I4.0. Therefore, this paper can provide a rationale
for understanding the range of interest and implications of
I4.0 applications in CI. Furthermore, it contributes to sys-
tematizing the existing knowledge about concepts that were
traditionally discussed separately (I4.0 and CI). It furthers the
trend towards integrating the same, makes a valuable theo-
retical contribution to the body of scientific literature in the
research field, and suggests directions for further study. This
will allow scholars and other interested parties to conduct
more complex research on the development of quantitative
assessment methods combining CI and I4.0, which are still
few and far between.
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In the context of existing scientific articles, the following
paper contributes to the present state of scientific knowledge
by providing a comprehensive and systematic review of liter-
ature pertaining to CI and I4.0 by:
- Rationalizing and systemizing the state-of-the-art
knowledge on the considered topics using the dynamic
Systematic Literature Network Analysis;
- Presenting the literature analysis in terms of its three
dimensions: (1) systematic review, (2) type and applica-
tion of reviewed study, and (3) bibliographic networks
of the literature review;
- Attempting to provide answers to research questions
addressed in current, relevant studies;
- Contributing to the existing body of research literature
focused on combining the concepts in question.
The paper is structured as follows. Section 2 presents the
research methodology and the bibliometric software used.
Then results of the systematic literature network analy-
sis are described in Section 3. Section 4 discusses results
derived from the SLNA-based reference framework illustrat-
ing the discovered CI and I4.0 relations. Directions for future
research are also described in Section 4, while Section 5 out-
lines the conclusions.
II. MATERIALS AND METHODS
A. SELECTION OF METHODS AND TOOLS
The dynamic development of scientific research in many
fields combined with its increasing interdisciplinarity has
contributed to the overall body of scientific knowledge, but
has also made it difficult for researchers to keep themselves
up to date with the current state of research. Limited cog-
nitive resources prevent a complete review of the literature,
and the selection of publications based on search engines
using specific ranking algorithms runs the risk of omitting
interesting papers with a low number of citations, but with
high potential impact. As a result, it becomes increasingly
difficult to obtain a reasonably comprehensive picture of
research in a given field and identify an interesting research
gap.
In such situations, data mining and machine learning meth-
ods can be employed, especially in terms of natural language
processing and analysis, knowledge extraction, and document
classification. Clustering and visualization techniques using
tools such as VOSviewer [61]–[63], topic modeling analysis
methods [64], or trend detection [65] are particularly popular
among researchers. The maturity and continuous improve-
ment of these methods encourages researchers to develop
methodologies for employing the same in literature review
processes as supplementary tools or even, in some cases,
in lieu of actually reading scholarly articles. For example,
Buchkremer et al. [66] proposed the STIRL (Generation
and Application of Systemic Taxonomies via Information
Retrieval and Semantic Learning) methodology, where they
use various data mining and machine learning methods in
the stages of information retrieval, taxonomy enhancement,
topics mapping, cleaning, corpus creation, evolution, topics
and trends identification, predictive analytics and results
presentation.
We employed a systematic literature review method, deep-
ened by Global Citation Score (GCS) analysis and network
analysis, by using the VOSviewer tool. This was followed by
Latent Dirichlet Allocation (LDA) to identify leading topics
of research conducted in the I4.0 and CI areas.
The literature search was conducted in two scientific
databases: Web of Science Core Collection (WoSCC)
and Scopus. The databases were chosen because they
are the most-commonly used when conducting literature
searches [67] and are also leading databases with significant
scientific impact scores. Due to their restrictive indexing
procedures, the documents returned from queries processed
in the databases tend to be of good quality [68]. The
databases are also considered to be the two most important
multidisciplinary bibliometric databases [69] used for field
delineation [70].
Due to evident similarities between the databases, many
authors have commented on their preference for one over the
other [71]. For example, Scopus has about 60% more records
and includes in-press articles. WoSCC is better when we want
to find more accurate citation information [72] and identify
’high-influence’ papers [73]. Since both databases have their
advantages and disadvantages, it was decided to use both in
the present study.
B. SYSTEMATIC LITERATURE REVIEW
A systematic literature review was chosen as a research
method to discover relations between I4.0 advancements and
issues relevant to critical infrastructure. A systematic review
was chosen as it entails strict procedures in searching for and
selecting papers to be reviewed, and is therefore ‘‘effective in
synthesizing what the collection of studies are showing in a
particular question and can provide evidence of the effect that
can inform policy and practice’’ [74].
The exploration of the existing literature on the relation-
ships (one-way and two-way) between CI and I4.0 was based
on the identification of available studies, which in turn was
facilitated by a specific set of keywords. The selection of
relevant papers for bibliometric research focused on the con-
struction of a search query covering various terms, synonyms,
and abbreviations related to the words ‘‘critical infrastruc-
ture’’ and ‘‘Industry 4.0’’. To identify all such relevant terms,
synonyms, and abbreviations, the authors analyzed the most
cited or recent literature reviews on critical infrastructure
[75]–[78] and Industry 4.0 [15], [12], [79], [80] available in
the WoSCC and Scopus databases.
The selection of keywords relevant to CI was based on
a keyword analysis drawing on 3,290 articles on the topic
published since 2018 [75]. The keyword selection was based
on the scoping study framework [81]. A scoping study is
designed to map the literature relevant to a subject or research
area to support the identification of key concepts, research
gaps, or evidence to inform practice, policymaking, and
research [82]. The discussed scoping study framework [81] is
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in line with other systematic review methodologies, e.g. the
PRISMA approach [83]. The search strings were iterated to
encompass a broad range of articles related to CI. This was
achieved by iteratively modifying the search string to either
include new keywords or add new restrictions. For example,
in some countries, the terms ‘‘lifeline systems’’ or ‘‘vital
societal function’’ are used synonymously to critical infras-
tructure [36], [84]. There is no real consensus as to exactly
which systems or institutions should be considered as critical
infrastructures, although different categorizations in national
policy frameworks show significant similarities [27], [29].
The eventual selection of keywords for CI was done using the
Article Score. The Article Score is developed based on the
principle that an article with many high-ranking keywords is
more relevant to a given research field than an article with
only a few low-ranking keywords. This resulted in a list of
CI-related keywords that were used to prepare the queries
for this paper. The original set of keywords was modified
by excluding the names of critical infrastructure systems,
i.e., transportation system, energy system, financial system,
etc. This procedure was done to find cross-cutting works on
multiple CI systems.
The term ‘‘Industry 4.0’’ is mainly used in Europe and is
often associated with the Fourth Industrial Revolution. The
concept of Industry 4.0 was first presented in 2011, and a
full description thereof was first published in 2013 [1]. The
core of Industry 4.0 is smart manufacturing, defined by the
National Institute of Standards and Technology (NIST) as
‘‘a fully integrated, collaborative manufacturing system that
responds in real-time to meet changing requirements and
conditions in the factory, in the supply chain, and the needs
of customers’’ [85]. On other continents, this paradigm is
most often referred to as ‘‘smart factory’’, ‘‘smart manu-
facturing’’ or ‘‘advanced manufacturing’’ [70]. The use of
different names results from national strategies that have
been developed in response to the need to increase the
competitiveness of national economies, especially in the
area of manufacturing. A full list of Industry 4.0 equivalent
programs is presented in the paper [3]. Literature reviews
from various journals were used to include all the common
terms, synonyms, and abbreviations applicable to ’Industry
4.0’, [3], [15], [79], [80]. There are also other, less popular
terms/synonyms related to Industry 4.0, such as industrial
Internet or industrial Internet of Things (IIoT), cyber manu-
facturing, digital transformation, cyber-physical (production)
system (CPS), cloud manufacturing, etc. [79]. It should be
noted that many terms treated as synonyms of Industry 4.0 are
correspond in fact to either its main technologies (IIoT, CPS,
big data) or its underlying purpose (digital transformation).
For this reason, such terms were not included in the query.
It is also worth noting that in the vast majority of papers, apart
from the specific terms mentioned above, the term Industry
4.0 itself also appears in the title/abstract/keywords.
In both cases (critical infrastructure and Industry 4.0),
abbreviations were omitted to include only papers where the
complete term appears in the abstract. In this case, adding
abbreviations would only artificially inflate the number of
results by including texts where those abbreviations are used
in other meanings. Based on the above keyword considera-
tions, the query was formulated for the search within titles,
keywords, and abstracts, without a time restriction. The query
was entered into the Scopus
TITLE −ABS −KEY
((‘‘critical infrastructure’’or ‘‘criticalbase’’
OR critical substructureOR critical services
OR key services OR key resources
OR ‘‘essential services’’ OR ‘‘crisis management’’)
AND
(‘‘Industrie 4.0’’ OR ‘‘Industry 4.0’’
OR 4th Industrial Revolution
OR Fourth Industrial Revolution
OR smart manufacturingorsmart factory
OR smart enterpriseorenterprise 4.0
OR ‘‘factory 4.0’’))
AND
LANGUAGE(english) (1)
and WoSCC databases on November 26, 2021. The dataset
obtained from the WoSCC database was fully contained in
the dataset obtained from Scopus, hence only the results from
the Scopus query are presented hereinbelow.
TITLE −ABS −KEY
((‘‘critical in frastructure’’ or‘‘criticalbase’’
OR critical substructureorcritical services
OR key servicesorkey resources
OR ‘‘essential services’’or ‘‘crisis management’’)
AND
(‘‘Industrie 4.0’’or‘‘Industry 4.0’’
OR 4th Industrial Revolution
OR Fourth Industrial Revolution
OR smart manufacturingorsmart factory
OR smart enterpriseorenterprise 4.0
OR ‘‘factory 4.0’’))
AND
LANGUAGE(english) (2)
This step is very important, because the results may change
if another query is used. This choice was made in line with
the aim of the paper, i.e., presenting the landscape of scien-
tific literature pertaining to the relationship between critical
infrastructure and Industry 4.0. The selected set of keywords
allowed the analysis of specific topics and their trends using
the adopted methodology.
Only studies in English (including papers in press) with
available abstracts and references were considered for further
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analysis (inclusion criteria). There were no other exclusion
criteria, so documents of all types could be considered and
no other restrictions were imposed in terms of the time of
publication, affiliations, etc. Altogether, 129 papers from
Scopus were considered in further analyses.
C. BIBLIOGRAPHIC NET WORK ANALYSIS USING
VOSVIEWER
We calculated the Global Citation Score (GCS) to detect
groundbreaking publications. GCS corresponds to the total
number of citations in the Scopus database. Studies with high
GCS are considered seminal or have a significant impact on
the area of knowledge to which they relate [86]. In other
words, GCS allows the identification of papers that form the
basis of a given field, which are often used by other authors to
develop their publications. Citations from the entire Scopus
database are counted, even if they are from articles that have
not been identified or selected.
To identify recent groundbreaking studies that could have
a potentially large impact and promising scientific input on
Industry 4.0 & critical infrastructure, papers were ranked
according to the number of citations received in the entire
Scopus database in 2021, divided by the number of years
since the year of publication. This allowed the identifica-
tion of those studies that have (potentially) low GCS but
have recently gained considerable interest from the scien-
tific community. This process ’weighed’ citations received in
2021 based relative to the ’lifespan’ of papers. The ranking
of papers prepared in this way is shown in Table 2.
We also performed a network analysis in terms of the
co-occurrence network for authors’ keywords and citation
network analysis using the VOSviewer approach and tool.
Co-occurrence analysis aims to analyze information char-
acteristics. It applies to words, authors, classifications, and
other record fields in books, journals, proceedings, and other
literature [87]. There are three basic types of co-occurrence
analyses [88]: (i) author co-occurrence (co-operation analy-
sis), (ii) author-keywords co-occurrence (coupling analysis),
(iii) keywords co-occurrence (co-word analysis). In the paper,
it was decided that the author’s keywords co-occurrence anal-
ysis will be used. This analysis allowed us to obtain the
results that are the most important from the point of view
of the purpose of the article. It concerns the analysis of
keywords indicated by authors in their studies. This method
of quantitative analysis allows one to discover the structure of
the research area within the considered set of papers and its
potential importance for the discipline. Due to the increas-
ingly accurate bibliographic indexing, co-word analysis is
widely used nowadays to analyze keywords in books and
journals. Author’s keywords co-occurrence analysis allows
one to obtain information on the number of times that given
keywords appeared simultaneously in a published article [89].
Co-occurrence of the author’s keywords creates a map in
which the size of the nodes corresponds to the frequency of
the keyword, while the lines show the relationships between
respective keywords [90]. A citation network is a network
where the nodes are papers, and the links mean that there are
citations between them. Hence, we can observe the flow of
knowledge as well as trace the citation connections between
papers. This, in turn, makes it possible to isolate clusters
(smaller networks), which include papers with least a single
connection with another paper within the cluster. Among
other reasons, this is done to facilitate easier definition of the
thematic scope of the cluster.
D. LATENT DI RICHLET ALLOCATION
This part of our study aimed to identify and analyze the
most important topics in the area of I4.0 usage in critical
infrastructure, its safety, and management using the Latent
Dirichlet Allocation (LDA) method. This provided the basis
for generating a fairly comprehensive representation of the
current research related to the discussed subject matter. Latent
Dirichlet Allocation is one of the most popular topic mod-
eling methods used in scientific research to identify key
research topics or research trends in fields such as medical
sciences, software engineering, political sciences, geogra-
phy, or enterprise architecture [91], [92]. First introduced
by Blei, Ng, and Jordan [93], it is a generative probabilistic
model of a corpus. It represents topics by word probabilities,
and the words with the highest probabilities in each topic
serve as an idea of the topic characteristics. To make the
interpretation easier, Chuan, Manning, and Heer introduced
Termite: a method for visualizing and interpreting topics [94],
which later inspired Sievert and Shirley to create LDAvis:
one of the most popular methods used for LDA results
interpretation [95].
The input for the LDA analysis was a clean dataset contain-
ing Authors, Titles, and Abstracts from the Scopus database.
LDA was used to analyze all the identified papers discussing
applications of the I4.0 toolset in Critical Infrastructure man-
agement extracted from Scopus using (1).
In our analysis, we used an open-source PyCaret
library [96] which utilizes a reliable LDA algorithm imple-
mentation supported by the LDAvis visualization technique.
In the first step, we initiated the model with the most pop-
ular irrelevant words (e.g., use, paper, research, start, etc.)
as the so-called stop-words. Next, we performed an intrin-
sic evaluation and computed a coherence value to iden-
tify the optimal number of topics. The highest coherence
score (=0.35) we obtained for four topics. The research
procedure used in the article is illustrated in Fig. 1.
E. OTHE R METHODS
In our analysis, we also applied two other topic modeling
and knowledge extraction methods: BERTopic and Knowl-
edge Graphs. BERTopic, a topic modeling technique based
on the BERT (Bidirectional Encoder Representations from
Transformers) model [97] resulted in an exceptionally high
number of outliers (75 out of 129 articles did not fit into any
of the topics). On the other hand, knowledge graphs generated
with the use of a SpaCy.io library [98] displayed a very high
number of relations making it very difficult to infer topic
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TABLE 1. The incidence of ‘‘critical infrastructure’’ and ‘‘Industry 4.0’’ topics in scientific databases as at Sep. 1, 2021.
FIGURE 1. The research procedure used in the article.
groups. That is why in this paper, we limited our analysis to
LDA and VOSviewer.
The initial results for BERTopic and knowledge graphs
justified our decision to focus solely on LDA application to
the I4.0 toolset (methods, technologies, tools) in our Criti-
cal Infrastructure review: interested readers can find a more
in-depth LDA presentation in e.g. [92], [93], [95].
III. RESULTS
A. GENERAL POPU LARITY OF TOPICS
Given that the relationship between CI and I4.0 is such a niche
topic, it was initially decided to search the Scopus and Web of
Science Core Collection databases only for ‘‘critical infras-
tructure’’, for ‘‘Industry 4.0’’, and for a conjunction of the
same. Under these criteria, the number of papers identified
oscillated between 700,000 and 800,000. The results for the
full terms ‘‘critical infrastructure’’ and ‘‘Industry 4.0’’ found
in the titles, abstracts, and keywords of papers listed in the
Scopus and Web of Science Core Collection databases are
presented in Table 1.
Despite the much larger total number of texts on criti-
cal infrastructure and Industry 4.0 in the Scopus database
(see Table 1), the proportions of texts tackling both issues to
the summarized number of all found papers are ca. 2.0%◦
(Scopus) and 1.5%◦(WoS CC). That was a good symptom –
because it indicated that in both databases the subject of CI
& I4.0 taken jointly is rarely discussed. The above consid-
erations proved that critical infrastructure and Industry 4.0
are both separately considered as highly important and inter-
esting. However, cross-thematic research tackling the same
jointly seems to be in short supply. There is a gap in the body
of knowledge regarding the impact of Industry 4.0 on crit-
ical infrastructure, its safety, and management. Meanwhile,
both research directions are of crucial interest to modern
economies. Therefore, one has to ask if Industry 4.0 technolo-
gies can support critical infrastructure, its safety, and manage-
ment, or not, and whether I4.0 solutions may be considered
a part of the critical infrastructure themselves. It is worth
discussing the promises and potential of I4.0 as well as the
existing threats stemming from its application within critical
infrastructure systems.
Other popular databases were also examined for the
query (‘‘critical infrastructure’’ and ‘‘Industry 4.0’’), but
results were scarce (EBSCOhost – 3 papers, IEEE Xplore –
11 papers).
B. BIBLIOGRAPHIC N ETWORK ANALYSIS USING
VOSVIEWER
The Global Citation Score (GCS) is used to determine the
group of leading flares in the analyzed study area and to detect
groundbreaking publications. Table 2 presents 10 of the most
frequently cited papers ranked by their GCS in the Scopus
database.
The most seminal works accordingly to GCS are presented
in Table 2. A paper Sadeghi et al. [99] was by far the highest
ranking of the lot. Another ranking of papers was constructed
to identify recent groundbreaking studies that could have a
potentially significant impact and promising scientific input
on Industry 4.0 & critical infrastructure. The ranking based on
citations in 2021 divided by years since publication (Table 3)
identified four articles [100]–[103] that were not previously
included in the GCS ranking (II). It is also important to
notice that high GCS values did not always correspond to
studies with a large impact and promising scientific input
on I4.0 & CI.
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TABLE 2. The global citation scores of the 10 most cited papers.
Based on the GCS, recent groundbreaking publications
lean towards topics related to the Internet of Things
(IoT) [102], [104], Industrial IoT systems [99], [107], Cyber-
Physical Systems (CPSs) as a part of IoT-oriented infrastruc-
ture [106], [108], and Industrial Control Systems (ICS) [112].
One paper distinguished by a very high number of citations
was also published early [99], i.e. they had initiated a sci-
entific discussion on the security, privacy challenges, and
cybersecurity themes. These are undoubtedly the main areas
discussed in the most quoted papers. Sub-themes include
issues related to the uses of IoT, IIoT, CPSs, and other Indus-
try 4.0 technologies in the management of critical infras-
tructure, cities (smart cities), or entire economies. There are
also studies that only to a very small extent concern critical
infrastructure. In the same, the potential of Industry 4.0 is
shown in the context of sustainable production and circular
economy [110] as well as strategies for providers and users
of Industry 4.0 [105].
TABLE 3. Ranking of the 10 most cited papers in 2021.
It is worth noting that two papers [101], [102] already have
10 or more citations despite having been published as recently
as in 2021.
The reference number of keywords (three) was adopted
in accordance with proposals tested in previous studies
[113], [114]. Using the VOSviewer program, a network
(Fig. 2) consisting of 20 nodes corresponding to 4 clusters
was obtained. In Fig. 2, each cluster is highlighted using
a different color. Occurrences were used as weights. The
size and clarity of a node corresponds to the frequency of
its occurrence in the analyzed set. In turn, the proximity of
particular elements indicates more frequent co-occurrence in
specific sets as compared to the more distant elements.
The minimum number of authors’ keywords in the set of
selected documents was 3. If a higher value were selected, the
number of keywords and clusters identified would decrease,
which could lead to the omission of an important issue that
has not yet been sufficiently investigated and described or is
simply not properly exposed in the paper. For example, if the
minimum number of author’s keywords in a set of selected
documents was set to 4, the query would return 13 keywords
and 4 clusters, and for the value of 5, there would only be
8 keywords and 3 clusters. Conversely, setting a value lower
than 3 would return too many words as keywords.
To understand the research trajectories, keywords are listed
according to their total link strength, i.e. their importance
in the cluster [115]. There were 75 links in the developed
co-occurrence network and the total link strength was 99.
The total link strength attribute indicates the total strength
of the co-occurrence of a given keyword with other keywords.
The higher the value, the more frequently a given keyword
coexists with others and is more relevant to the network.
Detailed information on the selected author’s keywords is
provided in Table 4.
The obtained clusters were described with reference to
the papers in which the searched keywords appeared. This
allowed us to present the results of research in given areas
related to Industry 4.0 and critical infrastructure. The result-
ing clusters delineated by the authors’ keywords are presented
in Table 5. The aggregation results are discussed in the dis-
cussion section.
Fig. 3 shows a citation network based on the selected
papers, using an overlay visualization. As a result, it became
possible to identify publications with the largest number
of links with others (weights) within the entire network
(129 papers). At the same time, the total number of citations
in the Scopus database was presented using a color scale
(from 0 - blue to 20 citations - yellow).
As we can see in Fig. 3, there was no greater network
of citations, and the connected citations formed clusters
of only up to 2 papers (5 such mini clusters were identi-
fied). Those instances indicate cases where a topic already
discussed by one author was elaborated on by another.
Klingenberg et al. [100] reviewed Industry 4.0 technologies
for a data-driven paradigm wherein the analyzed technologies
included, inter alia, Industrial Control Systems and IoT [112].
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FIGURE 2. Co-occurrence network of author’s keywords (minimum number of occurrences of a keyword: 3) created in VOSviewer.
Popkova et al. [104] presented a model of state manage-
ment in an IoT-based economy, and Tagirovet al. [116] pro-
posed development scenarios for regions relying on Digital
Economy. One study [117] addressed Industry 4.0 and
national security issues, while another paper by the same
team [118] presented considerations regarding cryptocur-
rency and national security. Montalban et al. [119] described
non-orthogonal multiple access (NOMA) in combination
with the 802.11n standard, and Forenbacher et al [120]
described the results of a laboratory analysis on the use of
an IEEE 802.11 wireless network in the presence of wireless
audio transmissions. Another study [99] discussed the issues
of security and privacy challenges in IIoT, while [121] dis-
cussed the issue of securing emergent IoT applications.
This may be seen as evidence to considerable dispersion
of research, as well as disaggregation of the results obtained.
Furthermore, no major direction of research could be iden-
tified as the respective topics were quite distant from each
other. This may have been due to the fact that the authors all
focused on rather narrow areas of critical infrastructure.
C. TOPICS IDENTIFIED USING LATENT DIRICHLET
ALLOCATION
We employed the LDAvis method to identify and analyze the
most important topics in the area of I4.0 usage in critical
infrastructure management [76]. Fig. 4, Fig. 5, Fig. 6, and
Fig. 7 present characteristics of the corresponding topics.
There were 42 articles under Topic 1, which corresponded
to 31.9% of the studies analyzed. The prominent words in
terms of frequency of occurrence in Topic 1 were systems,
industry, security, technology, infrastructure, attack, critical,
and network. The keywords applicable to topic one clearly
suggest a focus on network technologies understood as the
critical infrastructure of industrial systems. The dominant
issues include cyber security and the types of attacks to
which the infrastructure that keeps industry running may be
susceptible.
There were 38 articles pertaining to Topic 2, which repre-
sented 29.9% of the studies analyzed. The prominent words
in terms of frequency of occurrence in Topic 2 were systems,
security, infrastructure, industry, critical, IoT, smart, cps,
challenge, and framework. The thematic scope of the second
set of papers can be boiled down to challenges faced by
industrial systems security, where the critical infrastructure
framework consists specifically of IoT, smart, CPS technolo-
gies. The papers in this collection extended the set of network
threats to include CPS vulnerabilities. At the same time,
the strong connection between IoT, CPS, and human factors
required to achieve the benefits of industrial transformation
towards I4.0 were emphasized.
There were 32 articles related to Topic 3, which constituted
25.1% of the studies analyzed. The prominent words in terms
of frequency of occurrence in Topic 3 were network, systems,
service, datum, critical, infrastructure, industry, cloud, and
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TABLE 4. Information about the author’s keywords analyzed in
VOSviewer.
smart. The papers classified under this selection pertained to
the system of intelligent network services processing data in
the computational cloud. The authors identified this system as
infrastructure critical to the industry according to the idea of
I4.0. However, there was no indication of specific technolo-
gies, as was the case for Topic 2. The indication of cloud com-
puting as a platform for the integration of data from various
systems was the element that distinguished papers classified
under Topic 3 from those related to Topic 1. Moreover, papers
under Topic 3 focused more on the network of mutual con-
nections and the model of cooperation of available network
services, omitting the aspect of security and vulnerability of
such services.
There were 17 articles pertaining to Topic 4, which repre-
sented 13.2% of the studies analyzed. The prominent words
in terms of frequency of occurrence in Topic 4 were industry,
technology, critical, security, infrastructure, model, network,
risk, and business. The papers classified under Topic 4 dis-
cussed network technologies as elements of infrastructure
critical to the industry according to the idea of I4.0 under
the modeling approach. Unlike other papers, the works in
this group focused on the issues of security management and
risks resulting from the utilization of I4.0 tools in the industry.
The works were less concerned with technical issues. The
discussion was shifted to issues related to the user of such
implemented solutions or economic justification for their
implementation.
IV. DISCUSSION
A. GENERAL FIN DINGS
Our expectation that the scientific discourse does indeed
include some deliberations related to the relations between
CI and I4.0 were confirmed. However, given the number
of works devoted to exclusively I4.0 or CI, the intersection
of these two topics proved surprisingly poorly explored and
limited to only approx. 100 works (see Table 1).
It is clear that both CI and I4.0, taken separately, are per-
ceived as highly significant by practitioners and researchers
alike. This is hardly surprising as both issues constitute
building blocks of modern economies. At the same time,
the small number of works considering CI and I4.0 jointly
demonstrates a shortage of transdisciplinary research ori-
ented towards the impact that I4.0 has on CI, its safety, and
management.
As follows from the citation analysis, the most cited work
was a publication by Sadeghi et al. [99]. It achieved a sig-
nificantly greater number of citations than any other text
in the research area investigated (see Table 2 ). However,
considering additional time factors in the analysis of signif-
icance (measured by the number of citations), allowed the
identification of additional breakthrough works [100]–[103]
that were not evident in the analysis of citation num-
bers as such. This means that the relatively early work by
Sadeghi et al. [99] initiated a continued discourse on top-
ics related to the challenges of security, safety, privacy,
and cybersecurity. However, the leading topics were those
focused on the (industrial) Internet of Things (IoT) and cyber-
physical systems (CPSs) as a part of infrastructure dedicated
to industrial control systems (ICSs).
Two papers [101], [102] were published fairly recently
(2021), but have already gained a relatively high number of
citations. Usually, the number of citations increases in the
years following the publication, which in this case suggests
some potential of the two works to become highly rele-
vant to the discourse on CI and I4.0. Wu et al. [101] pre-
sented a convergence of blockchain and edge computing for
secure and scalable industrial IoT considered as an element
of critical infrastructure in I4.0 systems. Due to the digital
transformation of I4.0 driven by smart factories, big data,
and machine learning, CI is becoming increasing dependent
on IoT devices, or IIoT in the context of I4.0, creating the
so-called CI with IoT or IoT CI. (The International Data Cor-
poration forecasts that by 2025, there will be approximately
41.6 billion active IoT devices, generating 79.4 zettabytes of
data). The authors of the study highlight two major prob-
lems. Firstly, industrial control systems (ICS) were originally
designed mainly for proprietary and closed infrastructures
without paying too much attention to security issues, as tra-
ditional CIs are sort of isolated and are not vulnerable to
cyberattacks. However, as these infrastructures connected
to the internet via IoT, they became vulnerable to a wide
range of cyberattacks, including Distributed Denial of Service
(DDoS), malware, breach attack, brute force attack, man-
in-the-middle attack, SQL injection, and phishing. These
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TABLE 5. Clusters based on the author’s keywords discovered in VOSviewer.
FIGURE 3. Citation network created in VOSviewer.
threaten the ability of ICSs to provide normal support for
services. Scalability is another challenge which ICSs were not
originally designed to handle. Given the remarkable increase
in the number of IoT devices and the volume of data they
collect and analyze, the traditional centralized manner of data
collection and analysis is becoming the bottleneck of ICSs.
The emerging blockchain and edge computing paradigms are
promising technologies that can tackle the above challenges
in terms of CI security and scalability. The convergence of the
two technologies is vital to providing the necessary computa-
tion and storage for IoT, while simultaneously guaranteeing
the security and scalability CI under I4.0. The authors also
identified the following future research directions:
1) The architecture of IIoT CIs:
a. Standard Application Programming Interface for
Application Developers;
b. Integrated Networking, Computing, Storage, and
Power Resource Allocation;
c. Network Economy (How to design a practical
solution for the convergence of edge computing
and blockchain, by considering network economy
factors, e.g., pricing mechanisms of real-world
applications);
2) Secure IIoT CIs:
a. Security Vulnerabilities of IIoT Devices;
b. Security Vulnerabilities of Blockchain;
c. Integration of AI to Secure IIoT CIs;
d. Data Privacy Preservation;
3) Scalable CIs:
a. Scalability of IIoT;
b. Scalability of Blockchain;
c. Coordination Across Disciplines.
Zografopoulos et al. [102] comprehensively analyzed the
security and safety of cyber-physical energy systems. Threats
were modeled to assess risks. Moreover, the model consid-
ered resources and their behavior under adverse scenarios
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FIGURE 4. Topic one characteristics visualized with LDAVis.
using specific metrics to prioritize vulnerabilities. The pre-
sented framework for modeling, simulating, assessing, and
mitigating attacks in a CPS was examined on the example of
four case studies representing possible scenarios of attacks
against energy CPS. The reasons behind the attention gained
by this paper have been three-fold:
1) APPLICATION DOMAIN
The importance of energy systems as operations domain,
their critical nature within the power grid infrastructure where
attacks can lead to disastrous consequences;
2) THEMATIC DOMAIN
The increasing importance of cyber-security as such, con-
sidering the rapidly growing number of digital solutions in
organizations, but also in individuals settings;
3) UTILITARIAN SPECIFIC
The presented computer simulation models allow practition-
ers to easily modify and adapt the scenarios to specific cases.
The analysis of the two papers corroborated the origi-
nal assumption that the issue of the safety and security of
cyber-physical systems is a highly relevant topic in research
pertaining to CI and I4.0.
There is an evident shortage of studies on CI and I4.0 fol-
lowing a more holistic approach, as evidenced by the network
analysis performed using VOSviewer software. The whole
citation network was composed of 75 links, and their total
strength was 99. Given the total number of works (129), this
proves the high granularity of isolated studies on separate
topics (see Fig. 3). The connected sub-networks of citations
consist of a maximum of two papers. Five such mini clusters
were identified. This evidences considerable dispersion of
research as well as disaggregation of the results obtained.
There is also no major direction of research, and topics are
quite distant from each other. This was mainly due to the nar-
rowed analyses focusing on specific I4.0 technologies limited
to specific CI applications. A holistic overview of different
issues pertinent to CI and I4.0 as a total paradigm is lacking.
I4.0 technologies (mainly CPS, IoT) are already ’critical’,
but absent from scientific literature and studies discussing
connections between CI and I4.0 issues.
The co-occurrence network consisted of six clusters
(C1-C6, see Table 5 ), but its analysis led to aggregation into
three final clusters (FC1-FC3), as described below.
B. TOPICS RESULTING FROM THE VOSVIEWER ANALYSIS
1) FC1 – SECURITY OF INDUSTRIAL CONTROL SYSTEMS
Final cluster 1 (FC1) corresponds to the initially identified
cluster C1 (see Table 5 ) which deals with general issues
related to security, with a particular focus on cybersecurity in
industrial control systems (ICSs). ICS is considered by many
authors to be the heart of critical infrastructure [122], [123]
because it is mainly responsible for supervisory control and
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FIGURE 5. Topic two characteristics visualized with LDAVis.
data collection (SCADA), process monitoring, and control
of system information flows in the industry. The impor-
tance of cybersecurity in this context has been discussed
in many papers [99], [101]–[103], [112], [124]. The cluster
also includes studies on software-defined networking issues,
which is an important element responsible for the security
of data transmitted within the network [108] and can be
a countermeasure for Address Resolution Protocol (ARP)
spoofing in Communication-Based Train Control (CBTC)
systems [125]. Testbeds play an important role in the pro-
cesses of cybersecurity systems verification or software
validation [102], [111], [125].
2) FC2 –I4.0 SOLUTIONS AS SUPPORTIVE CI ELEMENTS
The initially identified clusters 2, 3, 4, and 6 (see Table 5)
were merged into FC2 (final cluster 2) as they all pertain
to the same major thematic area: implementing Industry
4.0 technologies to support critical infrastructure. It should
be noted that in some of the papers, the authors observed
that the main technologies of Industry 4.0 support critical
infrastructure [103], [106], but in other studies technologies
such as CPSs [102], (I)IoT [101], [102], cloud computing
[100], [124], blockchain [101] were considered important
and inseparable elements of critical infrastructure as such.
In some publications, the authors explore the integration of
various I4.0 technologies in the context of CI, e.g. connec-
tions (industrial) IoT, and CPSs [126]. The respective texts
consider this topic at different levels, from the combina-
tion of I4.0 and CI at the level of entire economies (digital
economy) [116], through smart cities [108], to the level of
communication protocols enabling communication between
machines (OPC Unified Architecture – OPC UA) [127]. The
aspect of the relationship between I4.0 and CI that receives
the most attention revolves around cybersecurity and related
issues, e.g. intrusion detection [128].
3) FC3 – RELIABILITY, AND RESILIENCE OF CI
Final cluster FC3 corresponds to the initially identified clus-
ter C5 (see Table 5 ). FC3 reflects maintenance strategies in
the context of ensuring the continuity of operation of devices
classified as critical infrastructure, e.g. refrigeration units
in hospital buildings [129]. It also discusses cybersecurity
capabilities that ensure the resilience of critical infrastruc-
ture [124], as well as the alignment of AI with disaster
resilience management support systems [130]. An important
aspect of resilience is indicated in the paper [102], which
presents anomaly detection as an important category of ensur-
ing for the security of energy CPS.
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FIGURE 6. Topic three characteristics visualized with LDAVis.
C. TOPICS RESULTING FROM THE LDA ANALYSIS
The LDAvis method allowed the identification of four leading
topics in the area of I4.0 usage in CI management:
- T1– network technologies as CI of industrial systems
(see Fig. 4),
- T2 – security of I4.0-based CI in industrial systems
(where CI framework is specific IoT, smart, CPS tech-
nologies) (see Fig. 5, Fig. 6, and Fig. 7),
- T3 – smart network services processing data in cloud
computing (see Fig. 6),
- T4 – I4.0-based modeling for network technologies as
industrial CI (see Fig. 7).
D. MAPPING VOSVIEWER AND LDA RESULTS
Our analysis of results from VOSviewer and LDA revealed
that the findings were mutually consistent. The results from
VOSviewer and LDA are mapped in Fig. 8 below.
The conducted literature review revealed that researchers
and practitioners are divided as to which elements consti-
tute Industry 4.0, how these elements are interrelated, and
where Industry 4.0 specifically applies. Regardless of the
definition, the idea of industry 4.0 indicates a transition
from centralized production towards production that is highly
flexible and self-controlled. Kolberg and Zuehlke [9] present
Industry 4.0 as a further development of CIM and thus as
a network approach that complements CIM through ICT.
The integration of automation technologies supports this
approach, e.g., cyber-physical systems (CPS), collaborative
robots, cloud computing, and big data sets, with the pro-
duction environment via IoT [10]. This provides the oppor-
tunity to network the entire factory, creating an intelligent
environment with the efficiency and capacity far exceeding
the existing capabilities of manufacturing companies. While
this undoubtedly creates new opportunities, one must also
consider the new unknown risks that may arise in this context.
The analyzed research indicates that the issue of CI appears
in the context of technologies enabling the realization of the
Industry 4.0 paradigm. In particular, many papers elaborate
on the uses of network technologies, cyber-physical Systems,
IoT, and cloud computing. The available studies indicate that
Industry 4.0 is no longer a trend of the future. For many
enterprises, it has lain at the very heart of their strategic and
research agenda for five or more years [131]. In this context,
Industry 4.0 and the technologies enabling its implementa-
tion may soon be included in the category of CI on which
the proper functioning of the economy, society, and public
administration will depend.
At the same time, a substantial body of work already indi-
cates that the technologies considered to be the foundations
of I4.0 are currently widely used in systems classified as CI.
Examples of the most advanced applications include IoT and
CPS in the power industry, wastewater treatment systems,
or systems for transporting electricity, oil, and gas.
However, there were no works discussing the applications
of I4.0 technologies in systems such as food production, res-
cue services, medical care system, or public administration.
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FIGURE 7. Topic four characteristics visualized with LDAVis.
FIGURE 8. Mapping of VOSviewer and LDA results for CI and I4.0 research topics.
This is likely due to overall lack of papers focusing on
non-technical CI systems. They appear in literature only as
complementary elements to case studies discussing technical
systems [60]. Secondly, it simply is easier to apply I4.0 tech-
nologies in CI systems of a technical nature because the
problems occurring in these systems are analogous to those
observed in manufacturing companies.
As follows from the literature review, the central topic of
the current scientific discourse pertaining to the protection of
Industry 4.0 is the issue of cybersecurity. The works analyzed
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FIGURE 9. Mapping general relations between I4.0 and CI.
focused on identifying threats related to network technolo-
gies. The results revealed a field of study in its fledgling stage,
with a limited number of experts operating somewhat in iso-
lation and offering single-point solutions instead of taking an
integrated, holistic approach. In addition, deliberations on the
security of elements identified as essential to Industry 4.0 do
not consider all the threats to which the respective elements
of Industry 4.0 are susceptible. Available works focus on the
impact of single technologies supporting Industry 4.0 or the
role of humans in the new industrial reality. There are also no
practical guidelines or methods to consider when dealing with
different types of threats at the decision-making stage with a
view to lowering risk to an acceptable level. The available
works tend to provide theoretical considerations, identifying
success factors or barriers to applying technologies support-
ing Industry 4.0.
A few works present solutions as holistic cybersecurity
management where the decision-making model can select an
optimal portfolio of security safeguards. AI for minimizing
cybersecurity investment and the expected cost of losses from
security breaches in a supply chain [132].
Literature does not cover the impacts of CI needs on
the I4.0 paradigm and technologies development. There-
fore, Fig. 9 depicts only a one-directional relation between
I4.0 and CI. One expects that the missing direction of
interactions (CI to I4.0) ought to be covered in future
research.
In general, literature delivers atomized knowledge on I4.0
technologies employed to support the management of CI and
I4.0 applications as a part of CI (see relations between ‘‘Spe-
cific technologies’’ and ‘‘CI’’ entities in Fig. 9). However,
research on how the full I4.0 paradigm could impact different
types of CI is lacking (see relations between ‘‘Paradigm’’ and
‘‘CI’’ entities in Fig. 9).
The presented areas of research (Fig. 8) selected as a result
of a literature review may be the basis of further, much more
deepened research. Despite the existence of several papers in
separate areas, many issues still require significant effort to
researchers and practitioners.
Within FC1 and T2, future research should concern
the issue of cybersecurity [51, 126] and leaking of sen-
sitive data [46]. Blockchain technologies [21], [23], [26],
[46], [101] and Digital Twin [24, 59] can be very impor-
tant in this area. The development of IioT [101] will also
be very important, and in particular the use of CloudEdge
technology (data anonymization) [128]. Certainly, efforts will
also be carried out on improving existing or creating new
communication protocols, as well as the development of
SCADA [125], [127].
Within FC2, T1 and T3, the development of cloud process-
ing [100], [124] and faster processing of increasing amounts
of available data (Big Data) [46], [47] can be indicated for
key areas of future research. The continuous development of
CPSs [55], [56], [102], [103], [112] is also significant, which
currently constitute the basis for the functioning of many
enterprises and enable much faster data flow or shop floor
communication in real time.
Within FC3 and T4, very important works will concern
issues related to the integration of systems within CI, as well
as increasing their reliability and resilience [32], [36], [38],
[41], [42], [45], [53], [57], [58], [59]. AI can be an important
support here [51], [52], [66]. It should be noted that research
are increasingly conducted on critical infrastructure facilities
(e.g. hospitals, power plants), where reliability and resilience
are the most important aspects [129]. Everything indicates
that this trend will be maintained. An important aspect in
the context of CI facility safety is to conduct a holistic
research [25] considering either cyber security and physical
security, technical security, legal security, personal security
and business continuity.
V. CONCLUSION
There are not many works jointly covering both topics of
I4.0 and CI, but there are plenty discussing each of the topics
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separately. One can note the complete absence of holistic
works jointly addressing CI (not specific to any domain) and
I4.0 from a general perspective, where I4.0 is understood
as both solutions supporting CI management and solutions
constituting an intermittent part of CI itself. Moreover, the
current body of literature covers only selected I4.0 elements
and is often focused on specific technologies, instead of the
paradigmatic I4.0 itself and its full toolset of solutions and
technologies. However, not even all of the most promising
I4.0 aspects have been sufficiently discussed in the context
of CI. For example, there are scarcely any studies on com-
puter simulation modeling and digital twin applications and
potential. The main research directions pursued currently and
likely to remain dominant in the nearest future are oriented
towards security, reliability, and resilience issues of specific
I4.0 technologies considered as elements of CI or as tools
supporting CI management. One has to conclude that the real-
ity has now outpaced scientific research. Therefore, two main
directions for further study should be considered, 1/ including
also white papers and reports published on different levels
(e.g. by national agencies responsible for CI management,
etc.), and 2/ computer simulation modeling of I4.0 appli-
cations in CI systems. Both aspects are currently severely
lacking in our research and scientific literature. Core tech-
nologies for I4.0 not only affect CI security but are already
a key component thereof. This is particularly obvious in CI
systems responsible for electricity production and transmis-
sion, pipeline transport, petroleum processing, or wastewater
treatment. Therefore, it is necessary to undertake research
on the development of CI operation models with adequate
consideration of the full I4.0 paradigm. In this context, the
presented results provide the starting point for more in-depth
studies and may serve as an inspiration for the scientific
community. There is a need for a holistic framework of CI
and I4.0, but detailed case studies are also lacking, especially
in terms of simulation modeling of I4.0 and CI interactions.
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