Secure data in cloud with multimodal key generation

  • Authors

    • P Selvarani
    • N Malarvizhi
    2018-02-05
    https://doi.org/10.14419/ijet.v7i1.7.9382
  • Multimodal Bio Cryptographic Authentication, Local Binary Pattern, Hybrid Particle Swarm Optimization with Genetic Algorithm, Triple DES Algorithm, Cloud Storage Environment.

  • Abstract

    Data Security is the Major problem in Cloud Computing. In order to overcome the data security problem the proposed technique utilizes effective data storage using biometric-based cryptographic authentication to support the user authentication for the cloud environment. For user authentication here we are considering iris and fingerprint. Initially the feature values are extracted from the iris and fingerprint using local binary pattern and Minutiae extraction respectively. Local binary pattern operator works with the eight neighbors of a pixel, using the value of this center pixel as a threshold. Minutiae points are the major features of a fingerprint image and are used in the matching of fingerprints. These minutiae points are used to determine the uniqueness of a fingerprint image. Based on that the proposed feature values are extracted from the iris and fingerprint image. In order to improve the security, the suggested technique utilizes the optimal features. For selecting the optimal features hybrid particle swarm optimization and genetic algorithm (HPSOGA) is utilized. Particle swarm optimization (PSO) is a population based stochastic optimization technique. The system is initialized with a population of random solutions and searches for optima by updating generations. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. Genetic Algorithms (GAs) are adaptive heuristic search algorithm based on the evolutionary ideas of natural selection and genetics. In our proposed method these two optimization algorithm is hybrid for more secure. From the optimization algorithm the suggested technique selects the optimal features. and then the optimal features are used to encrypt the input data. For encryption and decryption, the proposed technique utilizes Triple DES algorithm. Finally the encrypted data is stored in cloud. The performance of the proposed technique is evaluated in terms of encryption and decryption time, memory utilization and overall execution time. Our proposed data storage using biometric-based authentication is implemented with the help of Cloud simulator in the working platform of java.

  • References

    1. [1] M. Lori, “Data security in the world of cloud computing,†Co-published by the IEEE Computer and reliability Societies, pp. 61–64, 2009.

      [2] Zhu, Bo; Guang Gong (2011). "MD MITM Attack and Its Applications to GOST, KTANTAN and Hummingbird-2". eCrypt.

      [3] S.M. Bellovin and M. Merritt, “Encrypted Key Exchange: Password-Based Protocols Secure Against Dictionary Attacks,†Proc. IEEE Symp. Security and Privacy, IEEE CS Press, 1992, pp. 72-84. https://doi.org/10.1109/RISP.1992.213269.

      [4] F. Hao, R. Anderson, and J. Daugman. Combining crypto with biometrics effectively. IEEE Transactions on Computers, 55(9):1081– 1088, 2006. https://doi.org/10.1109/TC.2006.138.

      [5] Trefný, Jirí, and Jirí Matas."Extended set of local binary patterns for rapid object detection." Proceedings of the Computer Vision Winter Workshop. Vol. 2010.

      [6] Goldberg, David (2002). The Design of Innovation: Lessons from and for Competent Genetic Algorithms. Norwell, MA: Kluwer Academic Publishers. ISBN 978-1402070983 https://doi.org/10.1007/978-1-4757-3643-4.

      [7] Kennedy, J. and Eberhart, R., “Particle Swarm Optimization,†Proceedings of the IEEE International Conference on Neural Networks, Perth, Australia 1995, pp. 1942-1945. https://doi.org/10.1109/ICNN.1995.488968.

      [8] William Stallings, “Cryptography and Network Security: Principles and Practiceâ€, Pearson Education/Prentice Hall, 5 th Edition.

      [9] K. Yang and X. Jia, “Data storage auditing service in cloud computing: challenges, methods and opportunities,†World Wide Web, vol. 15, no. 4, pp. 409–428, 2012. https://doi.org/10.1007/s11280-011-0138-0.

  • Downloads

  • How to Cite

    Selvarani, P., & Malarvizhi, N. (2018). Secure data in cloud with multimodal key generation. International Journal of Engineering & Technology, 7(1.7), 27-33. https://doi.org/10.14419/ijet.v7i1.7.9382

    Received date: 2018-02-04

    Accepted date: 2018-02-04

    Published date: 2018-02-05