T-RO 2022

Abstract: Cooperative multi-robot systems coordinate their motion by exchanging information through consensus schemes to achieve a common goal. In the event of stealthy cyber attacks, compromised measurements and communication broadcasts can hijack a portion or the entire system toward undesired states. However, in order for these attacks to be effective, they have to exhibit non-random characteristics that contradict the expected multi-robot system behavior. To deal with these hidden attacks, we propose a runtime monitoring framework that considers the signed residual, defined as the difference between the expected and the received information to identify and isolate unexpected non-random behavior within the multi-robot system. Specifically, the technique that we propose -- named Cumulative Sign (CUSIGN) detector -- monitors and compares changes in signed values of residual with their expected occurrences to detect inconsistencies and trigger alarms when an attack is discovered. Our results are validated theoretically by providing detection bounds and are demonstrated with simulations and experiments on swarms of unmanned ground vehicles (UGVs) under different attacks in comparison with state-of-the-art residual-based detection schemes.

Within robotics, multi-agent system coordination and swarming have long been studied, but have regained consideration attention to consider safety and security issues. Most multi-agent applications are designed without considering cyber-security issues, which perform operations with the assumption that all agents are cooperating. We propose a monitoring framework for multi-agent systems that detects and isolates compromised vehicles to enable the swarm to resiliently continue operations in the presence of stealthy communications and sensor attacks. Our paper has recently been published to the IEEE Transactions on Robotics (T-RO) within the Special Issue on Resilience in Networked Robotic Systems PDF.