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PreprintCited by 128IoT and Edge/Fog ComputingNetwork Security and Intrusion DetectionInternet of Things and AI

The DOI matches its Crossref record; 253 of the 260 references it cites were found in a registry or an index.

A Survey on Industrial Internet of Things Security: Requirements, Attacks, AI-based Solutions, and Edge Computing Opportunities

Open access
Alotaibi, Bandar·2023·Sensors
DOI 10.20944/preprints202307.0771.v1PMC PMC10490764
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Abstract

The Industrial Internet of Things (IIoT) paradigm is a key research area derived from the Internet of Things (IoT). The emergence of IIoT has enabled a revolution in manufacturing and production, through the employment of various embedded sensing devices connected with each other by an IoT network, along with a collection of enabling technologies such as artificial intelligence (AI) and edge/fog computing. One of the unrivaled characteristics of IIoT is the inter-connectivity provided to industries; however, this characteristic might open the door for cyber-criminals to launch various attacks. In fact, one of the major challenges hindering the prevalent adoption of the IIoT paradigm is IoT security. Inevitably, an increasing number of research proposals have been introduced over the last decade to overcome these security concerns. To obtain an overview of this research area, conducting a literature survey of the published research is necessary, eliciting the various security requirements and their considerations. This paper provides a literature survey of IIoT security, focused on the period from 2017 to 2023. We identify IIoT security threats and classify them into three categories, based on the IIoT layer they exploit to launch these attacks. Additionally, we characterize the security requirements that these attacks violate. Finally, we highlight how emerging technologies, such as AI and edge/fog computing, can be adopted to address security concerns and enhance IIoT security.

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Crossref · 10.20944/preprints202307.0771.v1

Cites

253 of 253 references verified0 citation errors · 0 not checkable

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Figures

Figure 1 Industry 4.0 utilizes various emerging technologies to improve industrial production.
Figure 1 Industry 4.0 utilizes various emerging technologies to improve industrial production.CC BY · PubMed Central
Figure 2 These papers (i.e., 243 articles) were carefully chosen to write this survey paper.
Figure 2 These papers (i.e., 243 articles) were carefully chosen to write this survey paper.CC BY · PubMed Central
Figure 3 The relationships between CPS, IoT, IIoT, industrial internet, and Industry 4.0.
Figure 3 The relationships between CPS, IoT, IIoT, industrial internet, and Industry 4.0.CC BY · PubMed Central
Figure 4 The interaction between edge platforms; the upper layer (cloud servers) and the lower layer (edge devices).
Figure 4 The interaction between edge platforms; the upper layer (cloud servers) and the lower layer (edge devices).CC BY · PubMed Central
Figure 5 Framework of the three traditional IIoT layers: perception, network, and application.
Figure 5 Framework of the three traditional IIoT layers: perception, network, and application.CC BY · PubMed Central

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Citations

Cites

1 retracted

Show all 260 references

Research works printed but not linked: 10

  1. [12]Rabbani M.M. Dushku E. Vliegen J. Braeken A. Dragoni N. Mentens N. Reserve: Remote attestation of intermittent iot devices Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems Coimbra, Portugal 15–17 November 2021 578 580
  2. [59]Stallings W. Brown L. Computer Security Principles and Practice 3rd ed. Pearson Upper Saddle River, NJ, USA 2015
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  4. [79]Ghorbani A.A. Lu W. Tavallaee M. Network Intrusion Detection and Prevention Advances in Information Security Springer New York, NY, USA 2010 223p
  5. [119]Xing K. Srinivasan S.S.R. Rivera M.J.M. Li J. Cheng X. Attacks and countermeasures in sensor networks: A survey Network Security Springer Boston, MA, USA 2010 251 272
  6. [202]Allix K. Bissyandé T.F. Klein J. Le Traon Y. Androzoo: Collecting millions of android apps for the research community Proceedings of the 13th International Conference on Mining Software Repositories Austin, TX, USA 14–15 May 2016 468 471
  7. [205]Alhawi O.M. Baldwin J. Dehghantanha A. Leveraging machine learning techniques for windows ransomware network traffic detection Cyber Threat Intelligence Springer Cham, Switzerland 2018 93 106
  8. [208]Maiorca D. Mercaldo F. Giacinto G. Visaggio C.A. Martinelli F. R-PackDroid: API package-based characterization and detection of mobile ransomware Proceedings of the Symposium on Applied Computing Marrakech, Morocco 4–6 April 2017 1718 1723
  9. [209]Sgandurra D. Muñoz-González L. Mohsen R. Lupu E.C. Automated dynamic analysis of ransomware: Benefits, limitations and use for detection arXiv 2016 1609.03020
  10. [239]Lipps C. Herbst J. Schotten H.D. How to Dance Your Passwords: A Biometric MFA-Scheme for Identification and Authentication of Individuals in IIoT Environments Proceedings of the ICCWS 2021 16th International Conference on Cyber Warfare and Security Online 25–26 February 2021 168

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Metadata

Authors
Alotaibi, B.
Affiliations
University of Tabuk (SA)
Corresponding author
Alotaibi, Bandar
ORCID
Alotaibi, Bandar
Venue
Sensors
Publisher
MDPI AG
Published
2023-07-12
Volume
23
Issue
17
Pages
7470-7470
ISSN
1424-8220 (ISSN-L)
DOI
10.20944/preprints202307.0771.v1
PMC
PMC10490764
OpenAlex
W4386220180
Cited by
128
References
260
Citations by year
2026: 54 · 2025: 46 · 2024: 25 · 2023: 3
FWCI
4.49
Type
journal article
Language
en
Open access
Licence
Locations
  • Sensors (publishedVersion, cc-by)
  • Preprints.org (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
  • Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
  • Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
Keywords
Industrial Internet of Things, IIoT security, security requirements, cyberattacks, attack classification, security threats, artificial intelligence for security, edge computing, fog computing, manufacturing cybersecurity

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