Deep learning algorithm based cyber-attack detection in cyber-physical systems-a survey
N. Valliammal,Barani Shaju +1 more
- 21 Dec 2018
- Vol. 5, Iss: 49, pp 489-494
TL;DR: This article presents a detailed survey of various deep learning algorithms proposed for CPSs to achieve cyber defense and provides a suggestion for further improvement of CPSs with more efficiently.
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Abstract: Over the last years, cyber-attack detection and control system design has become a significant area in cyber-physical systems (CPSs) due to the rapid growth of cyber-security challenges via sophisticated attacks like data injection attacks, replay attacks, etc. The effect of different attacks may provide system failure, malfunctioning, etc. As a result, an improved security system may require to implement the cyber defense system for upcoming CPSs. The different deep learning algorithm based cyber-attack detection schemes have been designed to detect and mitigate the different types of cyber-attacks through CPSs, smart grids, power systems, etc. This article presents a detailed survey of various deep learning algorithms proposed for CPSs to achieve cyber defense. At first, different algorithms developed by previous researchers are studied in detail. Then, a comparative analysis is carried out to know the limitations in each algorithm and provide a suggestion for further improvement of CPSs with more efficiently.
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Citations
Utilizing Deep Learning to Identify Potentially Dangerous Routing Attacks in the IoT
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TL;DR: Several different deep learning algorithms suggested for use in CPSs to accomplish cyber defense are reviewed and a comparison study is performed to determine the shortcomings and offer a recommendation for how further improvements to CPSs might be made more effectively.
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TL;DR: In this paper , the authors reviewed unsupervised, supervised, semi-supervised and reinforcement learning algorithms for addressing cloud security challenges, and examined some of the ML algorithms applied to CC security threats.
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Deep Learning-based Framework for Detecting Malicious Insider-Inspired Cyberattacks Activities in Organisations
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