A multi-layer resilient architecture for constrained autonomous vehicles subject to false data injections during long range missions

In this paper, the problem of safely driving an autonomous vehicle for long range missions despite malicious actions on the data shared with the remote side is considered. This operating scenario poses two key questions: the capability of the underlying control algorithm to be feasible until the mission is accomplished; the effectiveness of adequate countermeasures to contrast the anomalous dynamical system behavior resulting from unpredictable attack phenomena. These requirements are here addressed by designing a layered control architecture that takes advantage of three methodologies: model predictive control, data encryption and perturbation analysis.