Secure State Estimation against Stealthy Attack

Abstract

In this chapter, we consider the problem of inferring the system state from sensory data in an adversarial environment, where some of the sensors are compromised by an adversary and can report arbitrary readings. Our goal is to construct a secure state estimator, whose estimation error is bounded regardless of the adversary's action. This chapter is organized as follows: In Section 2.2, we consider the estimation problem in a static setting, where we try to estimate the state using the measurements collected at a single time step. The problem of estimating the state of a linear time-invariant system from sequential sensory data is further considered in Section 2.3.