1. Introduction I nformation security is generally accepted to be essential to modern business and technology, both for privacy of transactions and communications, as well as for defense against malicious intruders. Cryptography is the study of information security and the feasibility of communication over an insecure channel while preserving the secrecy of the infor- mation transmitted [1], [2]. Cryptographic techniques should offer at least the following three security features concerning data transmission: confidentiality, authentication and integrity. Confidentiality is fundamental—third parties are expected to see the encrypted data but should not be able to decipher it. Authentication methods allow the receiver to verify that the sender is legitimate. Lack of authentication makes systems vul- nerable to fraudulent transactions and denial of service attacks. Integrity of the transmitted data must be verifiable, i.e., the receiver should be able to check that no part of the message M. Arvandi, S. Wu, and A. Sadeghian Ryerson University, CANADA © ARTVILLE On the Use of Recurrent Neural Networks to Design Symmetric Ciphers Abstract: In this article, we describe an innovative form of cipher design based on the use of recurrent neural networks. The well-known characteristics of neural networks, such as par- allel distributed structure, high computational power, ability to learn and represent knowledge as a black box, are successfully applied to cryptography. The proposed cipher has a relatively simple architecture and, by incorporating neural networks, it releases the constraint on the length of the secret key. The design of the symmetric cipher is described in detail and its security is analyzed. The cipher is robust in resisting different cryptanalysis attacks and pro- vides efficient data integrity and authentication services. Simula- tion results are presented to val- idate the effectiveness of the proposed cipher design. Digital Object Identifier 10.1109/MCI.2008.919075 42 IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE | MAY 2008 1556-603X/08/$25.00©2008IEEE