Enhancing the Stealth of Load Redistribution Attacks: A Novel Cluster-Driven Approach

This letter proposes a novel cluster-driven bilevel Load Redistribution (LR) attack model in cyber physical power systems. The main goal is on overloading multiple transmission lines while maintaining a high level of stealth. The proposed model employs cluster-based approach to form distinct clusters, each representing different load patterns within the power system. This enables the design of attack vectors that seamlessly blend with these load patterns, thereby challenging advanced anomaly detection systems. The stealth of the attack is quantified by the Stealth Distance Index (SDI), ensuring that injected false data remain within the maximum permissible distance from the centroid of its corresponding cluster. The proposed model is validated on the modified IEEE 14-bus and 30-bus systems, demonstrating enhanced stealth capabilities in LR attacks.

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Publication Details

Journal
IEEE Systems Journal
Published
2025-04-09
DOI
https://doi.org/10.1109/jsyst.2025.3554205
Citations
1
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
1.49

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article

Enhancing the Stealth of Load Redistribution Attacks: A Novel Cluster-Driven Approach

Rohit Bhakar, Satish Sharma, Rohini Haridas, Chenghong Gu
1 citations
IEEE Systems Journal
Network Security and Intrusion Detection
1.49
article

Enhancing the Stealth of Load Redistribution Attacks: A Novel Cluster-Driven Approach

Rohit Bhakar, Satish Sharma, Rohini Haridas, Chenghong Gu
article en
1 citations

Abstract

This letter proposes a novel cluster-driven bilevel Load Redistribution (LR) attack model in cyber physical power systems. The main goal is on overloading multiple transmission lines while maintaining a high level of stealth. The proposed model employs cluster-based approach to form distinct clusters, each representing different load patterns within the power system. This enables the design of attack vectors that seamlessly blend with these load patterns, thereby challenging advanced anomaly detection systems. The stealth of the attack is quantified by the Stealth Distance Index (SDI), ensuring that injected false data remain within the maximum permissible distance from the centroid of its corresponding cluster. The proposed model is validated on the modified IEEE 14-bus and 30-bus systems, demonstrating enhanced stealth capabilities in LR attacks.

IEEE Systems JournalVol. 19(2)
University of Bath (GB), Malaviya National Institute of Technology Jaipur (IN)
Engineering and Physical Sciences Research Council
Openalex Percentile: Top 18%
Network Security and Intrusion Detection
1.49
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