Coding Schemes for Securing Cyber-Physical Systems Against Stealthy Data Injection Attacks
This addresses security for cyber-physical systems against intelligent attacks, but it is incremental as it builds on existing coding and detection methods.
The paper tackles the problem of detecting stealthy data injection attacks in cyber-physical systems by coding sensor outputs to increase estimation residues, showing that multiple feasible coding matrices exist and proposing time-varying matrices to counter attackers who estimate the coding.
This paper considers a method of coding the sensor outputs in order to detect stealthy false data injection attacks. An intelligent attacker can design a sequence of data injection to sensors and actuators that pass the state estimator and statistical fault detector, based on knowledge of the system parameters. To stay undetected, the injected data should increase the state estimation errors while keep the estimation residues small. We employ a coding matrix to change the original sensor outputs to increase the estimation residues under intelligent data injection attacks. This is a low cost method compared with encryption schemes over all sensor measurements in communication networks. We show the conditions of a feasible coding matrix under the assumption that the attacker does not have knowledge of the exact coding matrix. An algorithm is developed to compute a feasible coding matrix, and, we show that in general, multiple feasible coding matrices exist. To defend against attackers who estimates the coding matrix via sensor and actuator measurements, time-varying coding matrices are designed according to the detection requirements. A heuristic algorithm to decide the time length of updating a coding matrix is then proposed.