提出分布式检测方法，让机器人在断续通信下仍能抵抗欺骗攻击并稳定协作。
Distributed Detection of Adversarial Attacks for Resilient Cooperation of Multi-Robot Systems with Intermittent Communication
- 基于积分连通性约束设计分布式检测框架
- 保证系统在恶意节点被隔离后可实现快速一致与编队
- 适用于受阻塞攻击影响的动态通信网络
本文研究在存在欺骗攻击的对抗环境下，一群移动自主代理在网络连通性任意时变且可能因拒绝服务（DoS）攻击导致间歇连接时的共识与编队问题。通过给出网络连通性的显式积分边界，刻画了系统对特定类对抗攻击的韧性。研究表明，在时间上均匀保持积分连通性的条件下，只要恶意节点被检测并隔离，系统即可实现有限增益$\\(mathcal{L}_{p}$稳定，且达成一致与编队的速度为统一指数级。论文提出了一个具备理论保障的分布式、可重构恶意节点检测框架，确保剩余合作节点的弹性协作。仿真验证了理论结果的有效性。
原文摘要 · Abstract (English)
This paper concerns the consensus and formation of a network of mobile autonomous agents in adversarial settings where a group of malicious (compromised) agents are subject to deception attacks. In addition, the communication network is arbitrarily time-varying and subject to intermittent connections, possibly imposed by denial-of-service (DoS) attacks. We provide explicit bounds for network connectivity in an integral sense, enabling the characterization of the system's resilience to specific classes of adversarial attacks. We also show that under the condition of connectivity in an integral sense uniformly in time, the system is finite-gain $\mathcal{L}_{p}$ stable and uniformly exponentially fast consensus and formation are achievable, provided malicious agents are detected and isolated from the network. We present a distributed and reconfigurable framework with theoretical guarantees for detecting malicious agents, allowing for the resilient cooperation of the remaining cooperative agents. Simulation studies are provided to illustrate the theoretical findings.
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