Learning with errors based dynamic encryption that discloses residue signal for anomaly detection

Abstract: Anomaly detection is a protocol that detects integrity attacks on control systems by comparing the residue signal with a threshold. Implementing anomaly detection on encrypted control systems has been a challenge because it is hard to detect an anomaly from the encrypted residue signal without the secret key. In this paper, we propose a dynamic encryption scheme for a linear system that automatically discloses the residue signal. The initial state and the input are encrypted based on the zero-dynamics of the system, so that the effect of encryption on the residue signal remains identically zero. The proposed scheme is shown to be secure in the sense that no other information than the residue signal is disclosed. Furthermore, we demonstrate a method of utilizing the disclosed residue signal to operate an observer-based controller over encrypted data for an infinite time horizon without re-encryption.