Chosen-Plaintext Cryptanalysis of a Clipped-Neural-Network-Based Chaotic Cipher

Abstract

In ISNN'04, a novel symmetric cipher was proposed, by combining a chaotic signal and a clipped neural network (CNN) for encryption. The present paper analyzes the security of this chaotic cipher against chosen-plaintext attacks, and points out that this cipher can be broken by a chosen-plaintext attack. Experimental analyses are given to support the feasibility of the proposed attack.

LNCS style, 7 pages, 1 figure (6 sub-figures)

Cited by in corpus (5)

• Cryptographic requirements for chaotic secure communications
• Breaking a chaotic image encryption algorithm based on modulo addition and XOR operation
• Cryptanalysis of an image encryption scheme based on the Hill cipher
• Using Echo State Networks for Cryptography
• Breaking a chaotic image encryption algorithm based on perceptron model