A Security-Enhanced Image Communication Scheme Using Cellular Neural Network

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

doi:10.3390/e23081000

Entropy (Jul 2021)

A Security-Enhanced Image Communication Scheme Using Cellular Neural Network

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

Affiliations

Heping Wen: Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan 528402, China
Jiajun Xu: Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan 528402, China
Yunlong Liao: Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan 528402, China
Ruiting Chen: Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan 528402, China
Danze Shen: Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan 528402, China
Lifei Wen: Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan 528402, China
Yulin Shi: Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan 528402, China
Qin Lin: Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan 528402, China
Zhonghao Liang: Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan 528402, China
Sihang Zhang: Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan 528402, China
Yuxuan Liu: Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan 528402, China
Ailin Huo: Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan 528402, China
Tong Li: Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan 528402, China
Chang Cai: Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan 528402, China
Jiaqian Wen: Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan 528402, China
Chongfu Zhang: Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan 528402, China

DOI: https://doi.org/10.3390/e23081000
Journal volume & issue: Vol. 23, no. 8
p. 1000

Abstract

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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.

Published in Entropy

ISSN: 1099-4300 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Science: Astronomy: Astrophysics; Science: Physics
Website: http://www.mdpi.com/journal/entropy

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