IEEE Trans Neural Netw Learn Syst. 2020 Sep;31(9):3334-3345. doi: 10.1109/TNNLS.2019.2943548. Epub 2019 Oct 17.
This article presents a secure communication scheme based on the quantized synchronization of master-slave neural networks under an event-triggered strategy. First, a dynamic event-triggered strategy is proposed based on a quantized output feedback, for which a quantized output feedback controller is formed. Second, theoretical criteria are derived to ensure the bounded synchronization of master-slave neural networks. With these criteria, an explicit upper bound is given for the synchronization error. Sufficient conditions are also provided on the existence of quantized output feedback controllers. A Chua's circuit is chosen to illustrate the effectiveness of our theoretical results. Third, a secure communication scheme is presented based on the synchronization of master-slave neural networks by combining the basic principle of cryptology. Then, a secure image communication is studied to verify the feasibility and security performance of the proposed secure communication scheme. The impact of the quantization level and the event-triggered control (ETC) on image decryption is investigated through experiments.
本文提出了一种基于事件触发策略的主从神经网络量化同步的安全通信方案。首先，提出了一种基于量化输出反馈的动态事件触发策略，形成了量化输出反馈控制器。其次，推导了理论准则，以确保主从神经网络的同步有界。利用这些准则，给出了同步误差的显式上界。还提供了量化输出反馈控制器存在的充分条件。选择蔡氏电路来说明我们理论结果的有效性。第三，通过结合密码学的基本原理，提出了一种基于主从神经网络同步的安全通信方案。然后，研究了安全图像通信，以验证所提出的安全通信方案的可行性和安全性能。通过实验研究了量化水平和事件触发控制（ETC）对图像解密的影响。
