Observer-based synchronization of memristive neural networks under DoS attacks and actuator saturation and its application to image encryption

作者：

Highlights：

• This is the first time to investigate the synchronization of memristive neural networks under denial-of-service attacks and actuator saturation.

• An observer-based control method is proposed for the state estimation and synchronization realization of memristive neural networks.

• By constructing Lyapunov function, sufficient conditions are derived to ensure the synchronization of memristive neural networks in the presences of denial-of-service attacks and actuator saturation.

• An image encryption scheme is proposed based on the derived synchronization theory, and the experimental results demonstrate that the scheme has a reliable performance.

摘要

•This is the first time to investigate the synchronization of memristive neural networks under denial-of-service attacks and actuator saturation.•An observer-based control method is proposed for the state estimation and synchronization realization of memristive neural networks.•By constructing Lyapunov function, sufficient conditions are derived to ensure the synchronization of memristive neural networks in the presences of denial-of-service attacks and actuator saturation.•An image encryption scheme is proposed based on the derived synchronization theory, and the experimental results demonstrate that the scheme has a reliable performance.

论文关键词：Synchronization,Memristive neural networks,DoS attacks,Actuator saturation,Image encryption

论文评审过程：Received 6 April 2021, Revised 15 January 2022, Accepted 7 March 2022, Available online 30 March 2022, Version of Record 30 March 2022.

论文官网地址：https://doi.org/10.1016/j.amc.2022.127080