Xiuying Li

A control problem of unknown nonlinear networked systems with false data injection attacks is studied in this paper. A multi-sensor fusion model-free adaptive control method with subjected to attacks based on I/O data is proposed, where the random false data injection attacks are estimated to enhance the control performance. Then the weights are optimally taken using an intelligent algorithm, moth-flame optimization algorithm. Finally, simulation is used to confirm that the suggested algorithm is available.

This article is concerned with the distributed H ∞ filtering problems with consensus for a class of systems subject to randomly occurred nonlinearity and time-varying topology in sensor networks where the nonlinearity considered can include the cyber attacks as a special case. A group of Bernoulli distributed random variables are utilized to describe the varying topology and missing measurements in a unified framework. In terms of two-dimensional (2-D) system theory in Rosser model, a nonlinear two-step filter is designed with consensus protocol where a multiple data strategy is used to improve the system performance. The desired filter parameters are obtained by LMI technique such that the filtering error system is asymptotically stable in the sense of mean square and meets a prescribed average H ∞ performance level. Finally, a simulation example demonstrates the effectiveness of the proposed algorithm.

This paper focuses on designing H ∞ filter for networked nonlinear systems subject to sensor saturations and packet dropouts. To capture the system uncertainties effectively, an interval type-2 (IT2) fuzzy model approach is applied. When the sensor outputs are lost during the transmission through the network links, the redundant channels are adopted to reduce the negative effect of packet dropouts. An IT2 filter is designed, where the membership functions and the number of fuzzy rules need not as the same as those of the plant, such that the filtering error system is guaranteed to be stochastically stable with prescribed H ∞ performance. Finally, an example is utilized to illustrate the effectiveness of the algorithm.

On the basis of the vulnerability of single point attack in the power analysis and the characteristics of energy leakage and cryptographic algorithm, a joint attack based on multiple points is proposed in this paper. To find two or more points that can be attacked in the cryptographic algorithm, the joint relationship between the attack points are established, with which the correct key in the algorithm are deciphered. The validation of the proposed method was demonstrated by using the Xor output of the SM4 cipher algorithm and the Sbox output to establish the intermediate function of the joint attack. The effectiveness of the multi-point joint attack is proved by the CPA analysis. In the experiment, the multi-point joint attack always outperforms the single point attack. For the multi-point joint attack, a 49.86% power consumption time decrease was observed compared with the two single point attack. For the attack success rate, the multi-point joint attack presents the optimal performance compared with the single point attack and the two single point attack.

The H ∞ controller design problem is studied for a class of network-based nonlinear systems represented by Takagi-Sugeno (T-S) fuzzy model. Due to the existence of network-induced transmission delays, there will be one packet or multiple packets even on packets arrived at the receiver side during one sampling period, which motivates the multiple packets compensation scheme for packet loss in this paper. Sufficient conditions are derived by using Lyapunov approaches and stochastic analysis, such that the asymptotic stability with a given disturbance attenuation level is guaranteed for the closed-loop systems. The desired controller parameters are obtained in terms of linear matrix inequalities (LMIs). Finally, an example is given to show the effectiveness of the algorithm.