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Artificial intelligence-based cyber security in the context of industry 4.0 : a Survey

Azambuja, Antonio João ; Plesker, Christian ; Schützer, Klaus ; Anderl, Reiner ; Schleich, Benjamin ; Almeida, Vilson Rosa (2023)
Artificial intelligence-based cyber security in the context of industry 4.0 : a Survey.
In: Electronics, 12 (8)
doi: 10.3390/electronics12081920
Article, Bibliographie

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Abstract

The increase in cyber-attacks impacts the performance of organizations in the industrial sector, exploiting the vulnerabilities of networked machines. The increasing digitization and technologies present in the context of Industry 4.0 have led to a rise in investments in innovation and automation. However, there are risks associated with this digital transformation, particularly regarding cyber security. Targeted cyber-attacks are constantly changing and improving their attack strategies, with a focus on applying artificial intelligence in the execution process. Artificial Intelligence-based cyber-attacks can be used in conjunction with conventional technologies, generating exponential damage in organizations in Industry 4.0. The increasing reliance on networked information technology has increased the cyber-attack surface. In this sense, studies aiming at understanding the actions of cyber criminals, to develop knowledge for cyber security measures, are essential. This paper presents a systematic literature research to identify publications of artificial intelligence-based cyber-attacks and to analyze them for deriving cyber security measures. The goal of this study is to make use of literature analysis to explore the impact of this new threat, aiming to provide the research community with insights to develop defenses against potential future threats. The results can be used to guide the analysis of cyber-attacks supported by artificial intelligence.

Item Type: Article
Erschienen: 2023
Creators: Azambuja, Antonio João ; Plesker, Christian ; Schützer, Klaus ; Anderl, Reiner ; Schleich, Benjamin ; Almeida, Vilson Rosa
Type of entry: Bibliographie
Title: Artificial intelligence-based cyber security in the context of industry 4.0 : a Survey
Language: English
Date: 30 June 2023
Publisher: MDPI
Journal or Publication Title: Electronics
Volume of the journal: 12
Issue Number: 8
DOI: 10.3390/electronics12081920
Corresponding Links:
Abstract:

The increase in cyber-attacks impacts the performance of organizations in the industrial sector, exploiting the vulnerabilities of networked machines. The increasing digitization and technologies present in the context of Industry 4.0 have led to a rise in investments in innovation and automation. However, there are risks associated with this digital transformation, particularly regarding cyber security. Targeted cyber-attacks are constantly changing and improving their attack strategies, with a focus on applying artificial intelligence in the execution process. Artificial Intelligence-based cyber-attacks can be used in conjunction with conventional technologies, generating exponential damage in organizations in Industry 4.0. The increasing reliance on networked information technology has increased the cyber-attack surface. In this sense, studies aiming at understanding the actions of cyber criminals, to develop knowledge for cyber security measures, are essential. This paper presents a systematic literature research to identify publications of artificial intelligence-based cyber-attacks and to analyze them for deriving cyber security measures. The goal of this study is to make use of literature analysis to explore the impact of this new threat, aiming to provide the research community with insights to develop defenses against potential future threats. The results can be used to guide the analysis of cyber-attacks supported by artificial intelligence.

Divisions: 16 Department of Mechanical Engineering
16 Department of Mechanical Engineering > Department of Computer Integrated Design (DiK) (from 01.09.2022 renamed "Product Life Cycle Management")
Date Deposited: 03 Jul 2023 06:39
Last Modified: 03 Jul 2024 02:59
PPN: 509235409
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