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Artificial Intelligence-Based Cyber Security in the Context of Industry 4.0 — A Survey

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
Artikel, Zweitveröffentlichung, Verlagsversion

Kurzbeschreibung (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.

Typ des Eintrags: Artikel
Erschienen: 2023
Autor(en): Azambuja, Antonio João Gonçalves de ; Plesker, Christian ; Schützer, Klaus ; Anderl, Reiner ; Schleich, Benjamin ; Almeida, Vilson Rosa
Art des Eintrags: Zweitveröffentlichung
Titel: Artificial Intelligence-Based Cyber Security in the Context of Industry 4.0 — A Survey
Sprache: Englisch
Publikationsjahr: 2023
Ort: Darmstadt
Publikationsdatum der Erstveröffentlichung: 2023
Verlag: MDPI
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Electronics
Jahrgang/Volume einer Zeitschrift: 12
(Heft-)Nummer: 8
Kollation: 18 Seiten
DOI: 10.26083/tuprints-00023791
URL / URN: https://tuprints.ulb.tu-darmstadt.de/23791
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Herkunft: Zweitveröffentlichung DeepGreen
Kurzbeschreibung (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.

Freie Schlagworte: artificial intelligence, cyber security, industry 4.0, machine learning, deep learning
Status: Verlagsversion
URN: urn:nbn:de:tuda-tuprints-237918
Zusätzliche Informationen:

This article belongs to the Special Issue AI in Cybersecurity

Sachgruppe der Dewey Dezimalklassifikatin (DDC): 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik
300 Sozialwissenschaften > 330 Wirtschaft
600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau
600 Technik, Medizin, angewandte Wissenschaften > 670 Industrielle und handwerkliche Fertigung
Fachbereich(e)/-gebiet(e): 16 Fachbereich Maschinenbau
16 Fachbereich Maschinenbau > Fachgebiet Product Life Cycle Management (PLCM)
Hinterlegungsdatum: 12 Mai 2023 08:13
Letzte Änderung: 15 Mai 2023 06:50
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