Abstract
Purpose of computer network is to share the information and provide the secure services. Due to publically in nature of computer network opens the possibility of hacking and stealing the confidential information by the attackers. To maintain confidentiality, integrity and to defend interception, fabrication, and modification of data become a burning issue. In this regard, many mechanisms have been proposed by researchers, among which Automatic Variable Key (AVK) is a novel approach. But in AVK initial key is distributed through Rivest-Shamir-Adleman (RSA). Thus, to surmount this initial distribution of key, we have proposed a new technique using Artificial Intelligence where the initial key is distributed to both the parties through fitness function of GA. To validate the proposed scheme, National Institute of Standards Technology (NIST) statistical tools is used to check the randomness among the auto-generated keys and is compared with existing related schemes. The Standard Deviation of Hamming distance is calculated for three different experiments and values obtained are 8.05, 6.44 and 7.05 which shows improvement in performance as compared to similar existing methods.
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Chunka, C., Goswami, R.S., Banerjee, S. (2019). A Novel Approach to Generate Symmetric Key in Cryptography Using Genetic Algorithm (GA). In: Abraham, A., Dutta, P., Mandal, J., Bhattacharya, A., Dutta, S. (eds) Emerging Technologies in Data Mining and Information Security. Advances in Intelligent Systems and Computing, vol 755. Springer, Singapore. https://doi.org/10.1007/978-981-13-1951-8_64
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DOI: https://doi.org/10.1007/978-981-13-1951-8_64
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