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
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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 |
| Zugehörige Links: | |
| 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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| Suche nach Titel in: | TUfind oder in Google |
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