Detection of replay attacks in autonomous vehicles using a bank of QPV observers

This paper addresses the problem of replay attack detection in autonomous vehicles. Due to the strong presence of nonlinearities, traditional approaches based on linear approximations of the dynamics would not work effectively. For this reason, the proposed approach is based on a bank of quadratic parameter varying (QPV) observers, designed in such a way that each observer is insensitive to a replay attack that affects one specific sensor channel. This feature allows the development of a decision algorithm, whose effectiveness is validated by means of simulation results.