Color Image Encryption Algorithm Using DNA Encoding and Fuzzy Single Neurons
Yaoqun Xu, Meng Tang · IEEE Access · 2022
In order to hide image information more efficaciously, improve the radio of workpiece and quality of encryption, this paper proposes delayed chaotic neuron dynamical system, extracts a single neuron research model to determine its dynamic properties, analyzes the model’s sensitivity, stability and the randomness of the chaotic sequence, and verifies its dynamics feasibility of combining the system with DNA encoding. The single delay neuron can simulate the unknown dynamic behavior and capability in the model in a certain sense which can effectively improve optimization ability and con-vergence speed of the neural to make the network more practical. DNA encoding also offers new train of thoughts and directions for the study of cryptography. In addition, by introducing the functional form of fuzzy number can further enhance the stability and adaptability of chaotic system in un-certain environment, and get more distinct chaotic phenomena. The experimental simulation and comprehensive data analysis of the algorithm are carried out in this paper. The data manifest that the system has a large chaotic range, can pass the randomness test of NIST and TestU01, has high complexity and sensitivity which could effectively avoid noise attacks. The encrypted information entropy of classical images can reach 7.9998, which confirms that it can effectively and safely realize the encryption of digital images.