Affiliations: College of Electronic Information Engineering,
Chongqing University of Science and Technology, Chongqing 400050, China.
pengjun70@126.com | Department of Computer Science, California State
University, Sacramento, CA 95819, USA. zhangd@ecs.csus.edu | Department of Computer Science and Engineering,
Chongqing University, Chongqing 400044, China. xfliao@cqu.edu.cn
Note: [] Address for correspondence: Chongqing University of Science and
Technology, Chongqing 400050, China
Abstract: Using Chaotic characteristics of dynamic system is a promising
direction to design cryptosystems that play a pivotal role in a very important
engineering application of cognitive informatics, i.e., information assurance
and security. However, encryption algorithms based on the lowdimensional
chaotic maps face a potential risk of the keystream being reconstructed via
return map technique or neural network method. In this paper, we propose a new
digital image encryption algorithm that employs a hyper-chaotic cellular neural
network. To substantiate its security characteristics, we conduct the following
security analyses of the proposed algorithm: key space analysis, sensitivity
analysis, information entropy analysis and correlation coefficients analysis of
adjacent pixels. The results demonstrate that the proposed encryption algorithm
has desirable security properties and can be deployed as a cornerstone in a
sound security cryptosystem. The comparison of the proposed algorithm with five
other chaos-based image encryption algorithms indicates that our algorithm has
a better security performance.
