Fuzzy and ant colony optimization based trust evaluation system for a cloud environment

  • Authors

    • R. Sivakami Anna University
    • A. Vincent Antony Kumar Anna University
    2018-11-14
    https://doi.org/10.14419/ijet.v7i4.9830
  • Believability Index, Cloud Computing, Evolutionary Algorithm, Trustworthiness, Trust Mechanism.
  • From consumers’ perspective, knowing the trust level of cloud service providers with maximum accuracy is often considered as a difficult task in cloud computing for security related arguments. The proposed trust evaluation system adopts the well-defined parameters for evalu-ating the trustworthiness of cloud service providers. This system employs fuzzy theory integrated with ant colony optimization. Initially, the believability index of each consumer is calculated. Then the fuzzy inference system is constructed for measuring the trust index of a cloud service provider. Several experiments were conducted and the results were analyzed to understand the impact of the four parameters on trust index. Then the system is applied for the developed cloud computing environment to show its efficiency. Experimental results demonstrate that the proposed system can give an effective solution to trust evaluation problems in open environments.

     

  • References

    1. [1] Lin G, Wang D, Bie Y, Lei M, “MTBAC: A Mutual Trust Based Access Control Model in Cloud Computingâ€, Communications China, (2014), pp.154-162.

      [2] Rizwana Shaikh, Sasikumar M, “Trust model for measuring security strength of cloud computing serviceâ€, Procedia Computer Science, 45, (2015), pp.380-389. https://doi.org/10.1016/j.procs.2015.03.165.

      [3] Tang C, Liu J, “Selecting a trusted cloud service provider for your SaaS programâ€, Computers & Security, 50, (2015), pp.60 - 73. https://doi.org/10.1016/j.cose.2015.02.001.

      [4] Huang J, Nicol D M, “Trust mechanisms for cloud computingâ€, Journal of Cloud Computing: Advances, Systems and Applications, Vol.2, No.9, (2013), pp.1-14.

      [5] Dan Pitt, “Trust in the cloud: The role of SDNâ€, Network Security, 3, (2013), pp.5-6. https://doi.org/10.1016/S1353-4858(13)70039-4.

      [6] Ranjit Bose, Xin (Robert) Luo, Yuan Liu, “The roles of security and trust: Comparing cloud computing and bankingâ€, Procedia – Social and Behavioral Sciences, 73, (2013), pp.30-34. https://doi.org/10.1016/j.sbspro.2013.02.015.

      [7] Dolev S, Gilboa N, Kopeetsky M, “Efficient private multi-party computations of trust in the presence of curious and malicious usersâ€, Journal of Trust Management, Vol.1, No.8, (2014), pp.1-21. https://doi.org/10.1186/2196-064X-1-8.

      [8] Meryeme Alouane, Hanan EI Bakkali, “Security, Privacy and Trust in cloud computing: A comparative studyâ€, IEEE International conference on cloud technologies and applications, (2015).

      [9] Priyadarsini R J, Arockiam L, “PBCOPSO: A Parallel Optimization Algorithm for Task Scheduling in Cloud Environmentâ€, Indian Journal of Science and Technology, Vol.8, No.16, (2015), pp.1-5. https://doi.org/10.17485/ijst/2015/v8i16/63248.

      [10] Dizaji Z A, Gharehchopogh F S, “A Hybrid of Ant Colony Optimization and Chaos Optimization Algorithms Approach for Software Cost Estimationâ€, Indian Journal of Science and Technology, Vol.8, No.2, (2015), pp.128-133. https://doi.org/10.17485/ijst/2015/v8i2/57776.

      [11] Chalotra S, Sehra S K, Brar Y S, Kaur N, “Tuning of COCOMO Model Parameters by using Bee Colony Optimizationâ€, Indian Journal of Science and Technology, Vol.8, No.14, (2015). Pp.1-5. https://doi.org/10.17485/ijst/2015/v8i14/70010.

      [12] Rezaeean A, Mirzaei A, Khozein A, “Optimization of Embankments by Ant Colony Optimization Algorithmâ€, Indian Journal of Science and Technology, Vol.5, No.1, (2012). pp.1863-1869.

      [13] Ghanbari A, Kazemi S M R, Mehmanpazir F, Nakhostin M M, “A Cooperative Ant Colony Optimization-Genetic Algorithm approach for construction of energy demand forecasting knowledge-based expert systemsâ€, Knowledge-Based Systems, 39, (2013), pp.194-206. https://doi.org/10.1016/j.knosys.2012.10.017.

      [14] Sivakami Raja, Saravanan Ramaiah, “2S-FAT based DLS Model for Cloud Environmentâ€, Arabian Journal for Science and Engineering, Vol. 41, No. 8, (2016), pp.3099-3112. https://doi.org/10.1007/s13369-016-2084-8.

      [15] Sivakami Raja, Saravanan Ramaiah, “CCDEA: Consumer and Cloud – DEA Based Trust Assessment Model for the Adoption of Cloud Servicesâ€, Cybernetics and Information Technologies, Vol. 16, No. 3, (2016), pp. 52-69. https://doi.org/10.1515/cait-2016-0034.

      [16] Chiregi, M., Jafari Navimipour N., “Cloud computing and trust evaluation: A systematic literature review of the state-of-the-art mechanismsâ€, Journal of Electrical systems and Information Technology (2017).

      [17] Wei C P, Tang X, “Possibility Degree Method for Ranking Intuitionistic Fuzzy Numbersâ€, IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, Toronto (2010), pp. 142-145.

      [18] Eucalyptus. http://www.eucalyptus.com.

  • Downloads

  • How to Cite

    Sivakami, R., & Vincent Antony Kumar, A. (2018). Fuzzy and ant colony optimization based trust evaluation system for a cloud environment. International Journal of Engineering & Technology, 7(4), 4335-4340. https://doi.org/10.14419/ijet.v7i4.9830