A Comprehensive Review on Deep Learning Techniques on Cyber Attacks on Cyber Physical Systems

Cyber-Physical Systems (CPSs), which integrate control, computing, and communication, are considered as next-generation intelligent systems.A major concern in CPS is to ensure security. If security is not ensured, then it leads to both property damage and casualties.Since CPS is closely associated w...

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Veröffentlicht in:SN computer science Jg. 5; H. 7; S. 891
Hauptverfasser: Sagar, Maloth, Vanmathi, C.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Singapore Springer Nature Singapore 01.10.2024
Springer Nature B.V
Schlagworte:
Algorithms
Casualties
Citation indexes
Communication
Computer Imaging
Computer Science
Computer Systems Organization and Communication Networks
Cyber-physical systems
Cybersecurity
Data Structures and Information Theory
Deep learning
Information Systems and Communication Service
Machine learning
Network security
Pattern Recognition and Graphics
Property damage
Regularization
Risk levels
Software Engineering/Programming and Operating Systems
Survey Article
Systematic review
Threats
Vision
Deep learning
Cyber-attack detection
CPS
Security threats
Risk analysis
Cyber security
Cyber-attack
ISSN:2661-8907, 2662-995X, 2661-8907
Online-Zugang:Volltext
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Zusammenfassung:Cyber-Physical Systems (CPSs), which integrate control, computing, and communication, are considered as next-generation intelligent systems.A major concern in CPS is to ensure security. If security is not ensured, then it leads to both property damage and casualties.Since CPS is closely associated with real life, it is a hot research area in present security research. Nevertheless, cyber security issues are also raised. More efforts are still required for understanding CPS security from a more comprehensive perspective even though there are several studies on CPS cybersecurity.To identify and detect cyber security in CPS, numerous methods have been applied. The majority of recently published studies focused on Machine Learning (ML) techniques, with little attention paid to the development of Deep Learning (DL). Hence, the analysis of cyber security on CPS utilizing several algorithms of DL techniques is systematically reviewed.The appropriate cyber security risk levels and their corresponding detection and mitigation processesare determined. This study could augment the adaptability of the system of CPS data. Also, it could increase the generalization of the models of security attacks in CPS. Using DL algorithms is strongly recommended by most authors as a means to identify cyber security issues in CPS.The CNN-centric LSTM, Deep Multi-architectural Approach, and DL-Meta classifier attained the highest accuracy in the detection rate of cyber security attacks in CPS when analogized with the other algorithms in DL techniques. Hence, for several critical systems in CPSs, the result renders clear guidelines to apply other regularization on DL techniques.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:2661-8907
2662-995X
2661-8907
DOI:10.1007/s42979-024-03253-x