Masquerade attack detection through observation planning for multi-robot systems
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Citation (published version)Kacper Wardega, Roberto Tron, Wenchao Li. 2019. "Masquerade Attack Detection Through Observation Planning for Multi-Robot Systems." AAMAS '19: PROCEEDINGS OF THE 18TH INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS. International Conference on Autonomous Agents and Multiagent Systems. Montreal, Canada, 2019-05-13 - 2019-05-17.
The increasing adoption of autonomous mobile robots comes with a rising concern over the security of these systems. In this work, we examine the dangers that an adversary could pose in a multi-agent robot system. We show that conventional multi-agent plans are vulnerable to strong attackers masquerading as a properly functioning agent. We propose a novel technique to incorporate attack detection into the multi-agent path-finding problem through the simultaneous synthesis of observation plans. We show that by specially crafting the multi-agent plan, the induced inter-agent observations can provide introspective monitoring guarantees; we achieve guarantees that any adversarial agent that plans to break the system-wide security specification must necessarily violate the induced observation plan.