Optimal Jamming Attack System Against Remote State Estimation in Wireless Network Control Systems

Recently, public attention is thoroughly aroused as to the security threats of Wireless Network Control System (WNCS), which can seriously disrupt the system operation. In order to achieve the attack effect that each sensor is damaged and maximize the terminal estimation error covariance, it is necessary to study an attack system from the attacker’s perspective. In this paper, we establish an attack system, which includes: the multi-sensor importance evaluation model, the time allocation of jamming attack, and the attack rules. Specifically, we firstly establish the wireless network control system model and the jamming attack model. Then, according to the transmission data and channel parameter information which is intercepted by the attackers, we establish an evaluation model of sensor based on the Mean Impact Value (MIV) algorithm. Then, based on the evaluation results of each sensor, we establish a distribution model of the number of attacks on each sensor. Then, we perform two jamming attack rules(continuous attack rule and good-sensor-late-attack rule)to attack each sensor. Finally, we use the attack system to conduct digital simulation experiments in first-order and high-order system. There is no different between the MIV-based sensor evaluation method in the multi-sensor importance evaluation experiment and sensor performance evaluation based on estimation error. In the jamming attack time allocation experiment, effect that every sensor was attacked had been achieved. In the attack rule experiment, we compare the experimental results of “continuous attack” and “ discontinuous attack”, and the result shows that the effect of “continuous attack” is better than that of “intermittent attack”. Similarly, we have conducted comparative experiments on all attack strategies, and the results show that “ good-sensor-late-attack ” strategy has the best effect. The effectiveness of the attack system is proved by digital simulation experiment.