Wireless Web Security Using a Neural Network-Based Cipher

Wireless Web Security Using a Neural Network-Based Cipher

Isaac Woungang (Ryerson University, Canada), Alireza Sadeghian (Ryerson University, Canada), Shuwei Wu (Ryerson University, Canada), Sudip Misra (Cornell University, USA) and Maryam Arvandi (Ryerson University, Canada)
Copyright: © 2007 |Pages: 25
DOI: 10.4018/978-1-59904-168-1.ch002
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Abstract

The increasingly important role of security for wireless Web services environments has opened an array of challenging problems centered on new methods and tools to improve existing data encryption and authentication techniques. Real-time recurrent neural networks offer an attractive approach to tackling such problems because of the high encryption capability provided by the structural hidden layers of such networks. In this chapter, a novel neural network-based symmetric cipher is proposed. This cipher releases the constraint on the length of the secret key to provide the data integrity and authentication services that can be used for securing wireless Web services communication. The proposed symmetric cipher design is robust in resisting different cryptanalysis attacks. Simulation results are presented to validate its effectiveness.

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