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

Content Provider	IEEE Xplore Digital Library
Author	Mandal, J.K. Sarkar, A.
Copyright Year	2011
Description	Author affiliation: Department of Computer Science & Engineering, University of Kalyani, 741235, Nadia, West Bengal, India (Mandal, J.K.; Sarkar, A.)
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 $2^{nd}$ 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.
Starting Page	62
Ending Page	67
File Size	948154
Page Count	6
File Format	PDF
ISBN	9781457707902
e-ISBN	9781457707926
DOI	10.1109/ReTIS.2011.6146841
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-21
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neurons Genetics Chaining Vectors Encryption Complexity theory Synchronization Adaptive Genetic Key based Neural Encryption (AGKNE) Wrapping Sub key Session key
Content Type	Text
Resource Type	Article

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