The Risk of Cyber Security for Power Stability Control System and Its Test Platform

Tong, Heqin; Xu, Jianbing; Zhang, Liquan; Liang, Shizhe; Mai, Cheng; Ding, Weidong; Hu, Kunxuan

doi:10.1109/icpics55264.2022.9873560

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Cited by 2 publications

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Load forecast anomaly detection under cyber attacks using a novel approach

Agarwal

2022

2022 IEEE 4th International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA)

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Load forecast anomaly detection under cyber attacks using a novel approach

Agarwal

2022

2022 IEEE 4th International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA)

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Improving Deceptive Patch Solutions Using Novel Deep Learning-Based Time Analysis Model for Industrial Control Systems

Tanyıldız,

Batur Şahin,

Batur Dinler

2024

Applied Sciences

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Industrial control systems (ICSs) are critical components automating the processes and operations of electromechanical systems. These systems are vulnerable to cyberattacks and can be the targets of malicious activities. With increased internet connectivity and integration with the Internet of Things (IoT), ICSs become more vulnerable to cyberattacks, which can have serious consequences, such as service interruption, financial losses, and security hazards. Threat actors target these systems with sophisticated attacks that can cause devastating damage. Cybersecurity vulnerabilities in ICSs have recently led to increasing cyberattacks and malware exploits. Hence, this paper proposes to develop a security solution with dynamic and adaptive deceptive patching strategies based on studies on the use of deceptive patches against attackers in industrial control systems. Within the present study’s scope, brief information on the adversarial training method and window size manipulation will be presented. It will emphasize how these methods can be integrated into industrial control systems and how they can increase cybersecurity by combining them with deceptive patch solutions. The discussed techniques represent an approach to improving the network and system security by making it more challenging for attackers to predict their targets and attack methods. The acquired results demonstrate that the suggested hybrid method improves the application of deception to software patching prediction, reflecting enhanced patch security.

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The Risk of Cyber Security for Power Stability Control System and Its Test Platform

Cited by 2 publications

References 6 publications

Load forecast anomaly detection under cyber attacks using a novel approach

Load forecast anomaly detection under cyber attacks using a novel approach

Improving Deceptive Patch Solutions Using Novel Deep Learning-Based Time Analysis Model for Industrial Control Systems

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