CDA: Covert Deception Attacks in Multi-Agent Resource Scheduling

In this letter, we address the critical security concerns in multi-agent systems, where illegal infiltration is commonly used to convert agents into malicious entities. Existing research predominantly focuses on explicit malicious attack patterns. Our work introduces a covert deception attack framework in the context of multi-agent resource scheduling scenarios. We first highlight vulnerabilities in scheduling strategies based on time and path costs. Exploiting these weaknesses, an infiltrated agent clandestinely gathers motion characteristics of other agents while posing as a teammate. Using these motion characteristics, the infiltrated agent employs an LSTM architecture to learn and predict congestion areas, thereby designing attack paths with greater time efficiency. This approach allows the infiltrated agent to secure additional resources and evade capture more effectively. Validation through simulation and real-world experiments demonstrates the feasibility and effectiveness of our approach, underscoring the importance of evaluating covert attacks in risk assessments within multi-agent systems.

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Publication Details

Journal
IEEE Robotics and Automation Letters
Published
2024-09-06
DOI
https://doi.org/10.1109/lra.2024.3455765
Citations
3
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
2.34

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article

CDA: Covert Deception Attacks in Multi-Agent Resource Scheduling

Lijun Chen, Wenjie Li, Jia Liu, Wei Hao
3 citations
IEEE Robotics and Automation Letters
Blockchain Technology Applications and Security
2.34
article

CDA: Covert Deception Attacks in Multi-Agent Resource Scheduling

Lijun Chen, Wenjie Li, Jia Liu, Wei Hao
article en
3 citations

Abstract

In this letter, we address the critical security concerns in multi-agent systems, where illegal infiltration is commonly used to convert agents into malicious entities. Existing research predominantly focuses on explicit malicious attack patterns. Our work introduces a covert deception attack framework in the context of multi-agent resource scheduling scenarios. We first highlight vulnerabilities in scheduling strategies based on time and path costs. Exploiting these weaknesses, an infiltrated agent clandestinely gathers motion characteristics of other agents while posing as a teammate. Using these motion characteristics, the infiltrated agent employs an LSTM architecture to learn and predict congestion areas, thereby designing attack paths with greater time efficiency. This approach allows the infiltrated agent to secure additional resources and evade capture more effectively. Validation through simulation and real-world experiments demonstrates the feasibility and effectiveness of our approach, underscoring the importance of evaluating covert attacks in risk assessments within multi-agent systems.

IEEE Robotics and Automation LettersVol. 9(11)
Nanjing University of Science and Technology (CN)
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 9%
Blockchain Technology Applications and Security
2.34
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CDA: Covert Deception Attacks in Multi-Agent Resource Scheduling — Lijun Chen, Wenjie Li, et al. · IEEE Robotics and Automation Letters (2024) | TGRS Research Map | TGRS