Hybrid Stealthy Attacks on Stochastic Event-Based Remote Estimation Under Packet Dropouts

Security related issues of cyber-physical systems are important and interesting from the perspectives of both attackers and defenders. In this paper, we design a stochastic event-based stealthy hybrid attack scheme for remote state estimation in the event of packet dropouts. The objective of the attacker is to maximize the performance degradation while remaining stealthy. Firstly, attack stealthiness is characterized based on the probability distribution and transmission rate. With the stealthiness constraints, an innovation-based stealthy attack model is designed under the assumption that attackers can intercept and modify the measurement innovations. Then, an optimal hybrid attack technique is proposed to maximize the estimation error. With the developed attack strategy, attackers can launch hybrid attacks, including denial-of-service attacks and/or false data injection attacks, to block the network communication channel and compromise the transmitted measurements, therefore degrading and even destroying the system performance. Verification examples are given to illustrate the effectiveness of the attack design performance.