Second Order State Hallucinations for Adversarial Attack Mitigation in Formation Control of Multi-Agent Systems
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arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866915353439764480 |
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| author | Patel, Laksh Raj, Akhilesh |
| author_facet | Patel, Laksh Raj, Akhilesh |
| contents | The increasing deployment of multi-agent systems (MAS) in critical infrastructures such as autonomous transportation, disaster relief, and smart cities demands robust formation control mechanisms resilient to adversarial attacks. Traditional consensus-based controllers, while effective under nominal conditions, are highly vulnerable to data manipulation, sensor spoofing, and communication failures. To address this challenge, we propose Second-Order State Hallucination (SOSH), a novel framework that detects compromised agents through distributed residual monitoring and maintains formation stability by replacing attacked states with predictive second-order approximations. Unlike existing mitigation strategies that require significant restructuring or induce long transients, SOSH offers a lightweight, decentralized correction mechanism based on second-order Taylor expansions, enabling rapid and scalable resilience. We establish rigorous Lyapunov-based stability guarantees, proving that formation errors remain exponentially bounded even under persistent attacks, provided the hallucination parameters satisfy explicit conditions. Comprehensive Monte Carlo experiments on a 5-agent complete graph formation demonstrate that SOSH outperforms established robust control schemes, including W-MSR and Huber-based consensus filters, achieving faster convergence rates, lower steady-state error, and superior transient recovery. Our results confirm that SOSH combines theoretical robustness with practical deployability, offering a promising direction for securing MAS formations against sophisticated adversarial threats. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_17283 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Second Order State Hallucinations for Adversarial Attack Mitigation in Formation Control of Multi-Agent Systems Patel, Laksh Raj, Akhilesh Systems and Control Multiagent Systems The increasing deployment of multi-agent systems (MAS) in critical infrastructures such as autonomous transportation, disaster relief, and smart cities demands robust formation control mechanisms resilient to adversarial attacks. Traditional consensus-based controllers, while effective under nominal conditions, are highly vulnerable to data manipulation, sensor spoofing, and communication failures. To address this challenge, we propose Second-Order State Hallucination (SOSH), a novel framework that detects compromised agents through distributed residual monitoring and maintains formation stability by replacing attacked states with predictive second-order approximations. Unlike existing mitigation strategies that require significant restructuring or induce long transients, SOSH offers a lightweight, decentralized correction mechanism based on second-order Taylor expansions, enabling rapid and scalable resilience. We establish rigorous Lyapunov-based stability guarantees, proving that formation errors remain exponentially bounded even under persistent attacks, provided the hallucination parameters satisfy explicit conditions. Comprehensive Monte Carlo experiments on a 5-agent complete graph formation demonstrate that SOSH outperforms established robust control schemes, including W-MSR and Huber-based consensus filters, achieving faster convergence rates, lower steady-state error, and superior transient recovery. Our results confirm that SOSH combines theoretical robustness with practical deployability, offering a promising direction for securing MAS formations against sophisticated adversarial threats. |
| title | Second Order State Hallucinations for Adversarial Attack Mitigation in Formation Control of Multi-Agent Systems |
| topic | Systems and Control Multiagent Systems |
| url | https://arxiv.org/abs/2506.17283 |