Chosen-Plaintext Cryptanalysis of a Clipped-Neural-Network-Based Chaotic   Cipher
  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. 
Chengqing Li, Shujun Li, Dan Zhang and Guanrong Chen