Masquerade attack detection through observation planning for multi-robot systems
Files
Accepted manuscript
Date
2019-05-13
DOI
Authors
Wardega, Kacper
Tron, Roberto
Li, Wenchao
Version
Accepted manuscript
OA Version
Citation
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.
Abstract
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.