Cyber Detectives: Determining When Robots or People Misbehave

This paper introduces a problem of validating the claimed behavior of an autonomous agent (human or robot) in an indoor environment containing one or more agents, against the observation history from a sparse network of simple, stationary sensors deployed in the same environment. Following principles of dynamic programming, we partition the decision problem into incremental search over a sequence of connectivity subgraphs induced by sensor recordings, which yields efficient algorithms for both single and multiple agent cases. In addition to immediate applicability towards security and forensics problems, the idea of behavior validation using external sensors complements design time model verification.

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