An adaptive genetic key based neural encryption for online wireless communication (AGKNE)

Abstract

In this paper, a genetic secret key based technique for neural encryption (AGKNE) has been proposed for online transmission of data/information in wireless communication. In this method both the communicating party receive the similar input vector, generate an output bit and are trained based on the output bit. Length of the key depends on the number of input and output neurons. Synchronized identical weight vectors are used to create chromosomes pool. Genetic secret key is generated on calculating the fitness function, which is the hamming distance between two chromosomes. GA operators like crossover and mutation are also used to add elitism of chromosomes. Plain stream passes through recursive modulo 2-substitution operation to generate intermediate cipher which is again encrypted using neuro genetic key to form the 2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">nd</sup> level cipher stream. Finally, chaining and cascaded xoring of neural key with the identical length intermediate cipher text is done to generate the cipher. Receiver will use identical neural weight secret key for performing deciphering process for generating the neuro genetic encrypted cipher text and secret key for decoding. Finally modulo-2 secret key uses to generate plain text. A session key based transmission has also been proposed using 161-bit key format of 14 different segments [7]. Parametric tests are done and results are compared in terms of Chi-Square test, response time in transmission with some existing classical techniques, which shows comparable results for the proposed system.