Method for secret communication of chaotic neural network under signal quantization circumstance

Abstract

The invention relates to a method for secret communication of a chaotic neural network under a signal quantization circumstance. The method comprises the following steps of (1) establishing a chaotic neural network model and a quantizer model; (2) constructing a state feedback controller to obtain an error dynamics system; (3) solving a controller gain matrix K and substituting into an actual controller to obtain a synchronous controller; (4) loading a ciphertext signal through a driving system in order to obtain a superposed signal and transmitting the superposed signal to a response system through a network; (5) making the driving system and the response system synchronous under the action of the synchronous controller; and (6) obtaining a recovered ciphertext signal through the superposed signal and a synchronizing signal. The method considers the uniform quantization phenomenon in the network environment and provides the synchronous controller, the driving system and the response system are synchronous under the action of the synchronous controller, and the recovered ciphertext signal is obtained through the superposed signal and the synchronizing signal after quantization, so that the impact of uniform quantization and random disturbance can be effectively eliminated and the secret communication can be carried out under the chaotic neural network model.

Description

technical field [0001] The invention belongs to the technical field of network communication, and relates to a neural network secure communication method, in particular to a chaotic neural network secure communication method under the condition of signal quantization. Background technique [0002] Since Pecora and Carroll discovered the synchronization method of chaotic systems in 1990, the application of chaos in secure communication has become a research hotspot in the field of information security. Chaotic signal can be used as the carrier of ciphertext information due to its characteristics of randomness, aperiodicity and unpredictability. Chaotic neural network usually has the characteristics of simple structure and complex dynamic performance, and is very suitable as a generator of chaotic signals. Therefore, the secure communication technology of chaotic neural network has broad application prospects. [0003] With the rapid development of computer network technology...

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Problems solved by technology

[0004] The present invention provides a chaotic neural network secure communication method under the signal quantization situation in view of the inability to deal with the problem of signal quantization in the existing chaotic secure communication process, which can effectively deal with uniform quantization and random disturbance in the chaotic secure communication process The impact

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