摘要
This paper proposes an image encryption algorithm LQBPNN(logistic quantum and back propagation neural network)based on chaotic sequences incorporating quantum keys. Firstly, the improved one-dimensional logistic chaotic sequence is used as the basic key sequence. After the quantum key is introduced, the quantum key is incorporated into the chaotic sequence by nonlinear operation. Then the pixel confused process is completed by the neural network. Finally, two sets of different mixed secret key sequences are used to perform two rounds of diffusion encryption on the confusing image. The experimental results show that the randomness and uniformity of the key sequence are effectively enhanced. The algorithm has a secret key space greater than 2182. The adjacent pixel correlation of the encrypted image is close to 0, and the information entropy is close to 8. The ciphertext image can resist several common attacks such as typical attacks, statistical analysis attacks and differential attacks.
This paper proposes an image encryption algorithm LQBPNN(logistic quantum and back propagation neural network)based on chaotic sequences incorporating quantum keys.Firstly,the improved one-dimensional logistic chaotic sequence is used as the basic key sequence.After the quantum key is introduced,the quantum key is incorporated into the chaotic sequence by nonlinear operation.Then the pixel confused process is completed by the neural network.Finally,two sets of different mixed secret key sequences are used to perform two rounds of diffusion encryption on the confusing image.The experimental results show that the randomness and uniformity of the key sequence are effectively enhanced.The algorithm has a secret key space greater than 2182.The adjacent pixel correlation of the encrypted image is close to 0,and the information entropy is close to 8.The ciphertext image can resist several common attacks such as typical attacks,statistical analysis attacks and differential attacks.
基金
supported by National Natural Science Foundation of China (No. 61402012)
Doctor Foundation of Anhui University of Science and Technology