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Issue title: Cognitive Informatics, Cognitive Computing, and Their Denotational Mathematical Foundations (I)
Article type: Research Article
Authors: Peng, Jun | Zhang, Du | Liao, Xiaofeng
Affiliations: College of Electronic Information Engineering, Chongqing University of Science and Technology, Chongqing 400050, China. [email protected] | Department of Computer Science, California State University, Sacramento, CA 95819, USA. [email protected] | Department of Computer Science and Engineering, Chongqing University, Chongqing 400044, China. [email protected]
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.
Keywords: Image encryption, cellular neural network, chaotic systems, security
DOI: 10.3233/FI-2009-0018
Journal: Fundamenta Informaticae, vol. 90, no. 3, pp. 269-282, 2009
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