Azambuja, Antonio João Gonçalves de ; 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, 2023, 12 (8)
doi: 10.26083/tuprints-00023791
Article, Secondary publication, Publisher's Version
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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 |
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Erschienen: | 2023 |
Creators: | Azambuja, Antonio João Gonçalves de ; Plesker, Christian ; Schützer, Klaus ; Anderl, Reiner ; Schleich, Benjamin ; Almeida, Vilson Rosa |
Type of entry: | Secondary publication |
Title: | Artificial Intelligence-Based Cyber Security in the Context of Industry 4.0 — A Survey |
Language: | English |
Date: | 2023 |
Place of Publication: | Darmstadt |
Year of primary publication: | 2023 |
Publisher: | MDPI |
Journal or Publication Title: | Electronics |
Volume of the journal: | 12 |
Issue Number: | 8 |
Collation: | 18 Seiten |
DOI: | 10.26083/tuprints-00023791 |
URL / URN: | https://tuprints.ulb.tu-darmstadt.de/23791 |
Corresponding Links: | |
Origin: | Secondary publication DeepGreen |
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. |
Uncontrolled Keywords: | artificial intelligence, cyber security, industry 4.0, machine learning, deep learning |
Status: | Publisher's Version |
URN: | urn:nbn:de:tuda-tuprints-237918 |
Additional Information: | This article belongs to the Special Issue AI in Cybersecurity |
Classification DDC: | 000 Generalities, computers, information > 004 Computer science 300 Social sciences > 330 Economics 600 Technology, medicine, applied sciences > 620 Engineering and machine engineering 600 Technology, medicine, applied sciences > 670 Manufacturing |
Divisions: | 16 Department of Mechanical Engineering 16 Department of Mechanical Engineering > Product Life Cycle Management (PLCM) |
Date Deposited: | 12 May 2023 08:13 |
Last Modified: | 15 May 2023 06:50 |
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