A Security-Enhanced Image Communication Scheme Using Cellular Neural Network |
| |
| Authors: | Heping Wen Jiajun Xu Yunlong Liao Ruiting Chen Danze Shen Lifei Wen Yulin Shi Qin Lin Zhonghao Liang Sihang Zhang Yuxuan Liu Ailin Huo Tong Li Chang Cai Jiaqian Wen Chongfu Zhang |
| |
| Affiliation: | 1.Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan 528402, China; (H.W.); (J.X.); (Y.L.); (R.C.); (D.S.); (L.W.); (Y.S.); (Q.L.); (Z.L.); (S.Z.); (Y.L.); (A.H.); (T.L.); (C.C.); (J.W.);2.School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China;3.Guangdong Provincial Key Laboratory of Information Security Technology, Guangzhou 510006, China |
| |
| Abstract: | In the current network and big data environment, the secure transmission of digital images is facing huge challenges. The use of some methodologies in artificial intelligence to enhance its security is extremely cutting-edge and also a development trend. To this end, this paper proposes a security-enhanced image communication scheme based on cellular neural network (CNN) under cryptanalysis. First, the complex characteristics of CNN are used to create pseudorandom sequences for image encryption. Then, a plain image is sequentially confused, permuted and diffused to get the cipher image by these CNN-based sequences. Based on cryptanalysis theory, a security-enhanced algorithm structure and relevant steps are detailed. Theoretical analysis and experimental results both demonstrate its safety performance. Moreover, the structure of image cipher can effectively resist various common attacks in cryptography. Therefore, the image communication scheme based on CNN proposed in this paper is a competitive security technology method. |
| |
| Keywords: | secure communication image encryption chaos cellular neural network |
|
|
