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A Novel Approach to Generate Symmetric Key in Cryptography Using Genetic Algorithm (GA)

  • Chukhu ChunkaEmail author
  • Rajat Subhra Goswami
  • Subhasish Banerjee
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 755)

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.

Keywords

Genetic algorithm Initial key AVK Artificial intelligence 

References

  1. 1.
    Shannon, C.E.: A mathematical theory of communication, Part I, Part II. Bell Syst. Tech. J. 27, 623–656 (1948)CrossRefGoogle Scholar
  2. 2.
    Shannon, C.E.: Communication theory of secrecy systems. Bell Lab. Tech. J. 28(4), 656–715 (1949)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Bhunia, C. T.: Application of AVK and selective encryption in improving performance of quantum cryptography and networks. United Nations Educational Scientific and Cultural Organization and International Atomic Energy Agency, retrieved, 10(12), p. 20010 (2006)Google Scholar
  4. 4.
    Bhunia, C.T., Mondal, G., Samaddar, S.: Theory and application of time variant key in RSA and that with selective encryption in AES. In: Proceedings of EAIT, pp. 219–221. Elsevier Publications, Calcutta CSI (2006)Google Scholar
  5. 5.
    Kumar, A., Chatterjee, K.: An efficient stream cipher using genetic algorithm. In: International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), IEEE, pp. 2322–2326 (2016)Google Scholar
  6. 6.
    Goswami, R.S., Chakraborty, S.K., Bhunia, A., Bhunia, C.T.: New approach towards generation of automatic variable key to achieve perfect security. In: 2013 Tenth International Conference on Information Technology: New Generations (ITNG), IEEE, pp. 489–491 (2013)Google Scholar
  7. 7.
    Goswami, R.S., Chakraborty, S.K., Bhunia, A., Bhunia, C.T.: New techniques for generating of automatic variable key in achieving perfect security. J. Inst. Eng. (India) Ser. B 95(3), 197–201 (2014)Google Scholar
  8. 8.
    Singh, B.K., Banerjee, S., Dutta, M.P., Bhunia, C.T.: Generation of automatic variable key to make secure communication. In: Proceedings of the International Conference on Recent Cognizance in Wireless Communication and Image Processing. Springer, New Delhi, pp. 317–323 (2016)Google Scholar
  9. 9.
    Dutta, M.P., Banerjee, S., Bhunia, C.T.: An approach to generate 2-dimensional AVK to enhance security of shared information. Int. J. Secur. Appl. 9(10), 147–154 (2015)Google Scholar
  10. 10.
    Banerjee, S., Dutta, M.P., Bhunia, C.T.: A novel approach to achieve the perfect security through AVK over insecure communication channel. J. Inst. Eng. (India) Ser. B 98(2), 155–159 (2017).  https://doi.org/10.1007/s40031-016-0264-2
  11. 11.
    Prajapat, S., Thakur, R.S.: Cryptic mining for automatic variable key based cryptosystem. In: 1st International Conference on Information Security and Privacy. Procedia Comput. Sci. 78, 199–209 (2016).  https://doi.org/10.1016/j.procs.2016.02.034
  12. 12.
    Xu, P., Cumanan, K., Dai, X.: Group secret key generation in wireless networks: algorithms and rate optimization. IEEE Trans. Inf. Forensics Secur. 11(8), 1831–1846 (2016)Google Scholar
  13. 13.
    Eli B.: A fast new DES implementation in software. In: Proceedings the of International Symposium on Foundations of Software Engineering, pp. 260–273 (1997)Google Scholar
  14. 14.
    Mondal, S., Mollah, T.K., Samanta, A., Paul, S.: A survey on network security using genetic algorithm. Int. J. Innov. Res. Sci. Eng. Technol. 5(1), 319–8753 (2016)Google Scholar
  15. 15.
    Subhrani, S., Niladri, S.C., Mandal, J.K.: Key based level genetic technique. In: 7th International Conference on Information Assurance and Security (IAS). IEEE (2012). ISBN: 978-1-4577-2154-0,  https://doi.org/10.1109/isias.2011.6122826
  16. 16.
    Jawaid, S., Jamal, A.: Generating the best fit key in cryptography using genetic algorithm. Int. J. Comput. Appl. (0975–8887) 98(20), 3339 (2014)Google Scholar
  17. 17.
    Kumar, A., Ghose, M.K.: Overview of information security using genetic algorithm and chaos. Inf. Secur. J. Glob. Perspect. 18(6), 306–315 (2009).  https://doi.org/10.1080/19393550903327558CrossRefGoogle Scholar
  18. 18.
    Soni, A., Agrawal, S.: Key generation using genetic algorithm for image encryption. Int. J. Comput. Sci. Mob. Comput. 2(6), 376383 (2013)Google Scholar
  19. 19.
    Sindhuja, K., Devi, S.P.: A Symmetric key encryption technique using genetic algorithm. J. Comput. Sci. Inf. Technol. 5(1), 414–416 (2014). ISSN: 0975-964Google Scholar
  20. 20.
    Bhowmik, S., Acharyya, S.: Image cryptography: The genetic algorithm approach. In: 2011 IEEE International Conference on Computer Science and Automation Engineering (CSAE), vol. 2, pp. 223–227 (2011)Google Scholar
  21. 21.
    Elaine, R., Kevin, K., Shivashankar, B.N.: Artificial Intelligence, 3rd edn. McGraw Hill Publication, India, (2008)Google Scholar
  22. 22.
    Rukhin, A., Soto, J., Nechvatal, J., Smid, M., Barker, E.: A statistical test suite for random and pseudorandom number generators for cryptographic applications. Booz-Allen and Hamilton Inc., Mclean Va (2010)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Chukhu Chunka
    • 1
    Email author
  • Rajat Subhra Goswami
    • 1
  • Subhasish Banerjee
    • 1
  1. 1.Department of Computer Science & EngineeringNational Institute of TechnologyYupiaIndia

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