False Data Injection Attack for Cyber-Physical Systems With Resource Constraint

Cyber-security is of the fundamental importance for cyber-physical systems (CPSs), since CPSs are vulnerable to cyber attack. In order to make the defensive measures better, one needs to understand the behavior from the view of an attacker. In this paper, the problem of false data injection attack on remote state estimation with resource constraints is studied in two cases, where the first case is that the attacker adds a Gaussian noise to the innovation, while the other is that the attacker employs a Gaussian noise to replace the innovation. In addition, the attacker is assumed to has a resource constraint, i.e., he/she cannot attack all the sensors, at the same time should decide which sensors to attack. By using the matrix theory, the optimal attack strategy problem, which aims to maximize the trace of the remote estimation error covariance, is converted into a convex optimization problem that can be solved. Thus, an optimal attack strategy is given to illustrate which sensors should be attacked. An example is given to show the effectiveness of the theoretical results.