An Adaptive Neural Network guided Random Block Length based Cryptosystem for online wireless communication (ANNRBLC)

In this paper an Adaptive Neural Network guided Random Block Length based Cryptosystem (ANNRBLC) has been proposed for online transmission of data/information through wireless communication. Both communicating networks receive an identical input vector, generate an output bit, networks are trained based on the bit, and as a result of this dynamics through adaptive weight vectors the networks synchronize to an identical time dependent weight vectors. This phenomenon is used to form a secured secret-key through a public channel. Three sub keys are generated during the process to encrypt string of random length (multiple of 64 blocks). Length of sub key 1, sub key 2, sub key 3 is 128 bit, 192 bit, and 256 bit respectively. Identical weight vectors are used to generate first sub key of 128 bit length. Subsequent sub keys are generated as intermediate steps of the technique using neural cryptosystem. A session key based transmission has also been proposed using 161 bit key format of 14 different segments [7,8]. 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.