Cryptanalysis of a chaotic neural network based multimedia encryption scheme

Authors:
Chengqing Li;Shujun Li;Dan Zhang;Guanrong Chen
Affiliations:
Department of Mathematics, Zhejiang University, Hangzhou, Zhejiang, China;Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China;College of Computer Science, Zhejiang University, Hangzhou, Zhejiang, China;Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China
Venue:
PCM'04 Proceedings of the 5th Pacific Rim conference on Advances in Multimedia Information Processing - Volume Part III
Year:
2004

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Abstract

Recently, Yen and Guo proposed a chaotic neural network (CNN) for signal encryption, which was suggested as a solution for protection of digital images and videos. The present paper evaluates the security of this CNN-based encryption scheme, and points out that it is not secure from the cryptographical point of view: 1) it can be easily broken by known/chosen-plaintext attacks; 2) its security against the brute-force attack was much over-estimated. Some experiments are shown to support the results given in this paper. It is also discussed how to improve the encryption scheme.