Abstract

Cooperative multirobot 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 nonrandom characteristics that contradict the expected multirobot system behavior. To deal with these hidden attacks, we propose a runtime monitoring framework that considers the signed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">residual</i> , defined as the difference between the expected and the received information to identify and isolate unexpected nonrandom behavior within the multirobot system. Specifically, the technique that we propose—named <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Cumulative Sign</i> 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 under different attacks in comparison with state-of-the-art residual-based detection schemes.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call