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Information Journal Paper

Title

Hybrid Method for Detecting Trustworthy Cloud Service Providers using Analytical Hierarchical Process and Neural Network

Pages

  105-122

Abstract

 Recently, cloud computing has become very popular. Due to this popularity, the number of Cloud services’ features is increasing continuously. To find a reliable provider in the cloud environment and select the best resources in the heterogeneous infrastructures, trust plays an important role. Customers distrust in Cloud service providers is considered as a barrier to Cloud service acceptance. This research develops a model for identifying invalid Cloud service providers, in which validation is examined using cloud providers’ trust evaluation features. In this approach, in order to detect cloud providers, the neural network method with a robust hierarchical weight estimation is proposed; analytical hierarchical process is being used for its capability in finding and detecting optimal values. The simulation results indicate an error rate of 0. 055%, showing this method to be more accurate compared to the state-of-the-art methods.

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    APA: Copy

    Tabaghchi Milan, S., & Jafari Navimipour, n.. (2019). Hybrid Method for Detecting Trustworthy Cloud Service Providers using Analytical Hierarchical Process and Neural Network. JOURNAL OF ELECTRONIC AND CYBER DEFENCE, 6(4 (24) ), 105-122. SID. https://sid.ir/paper/243141/en

    Vancouver: Copy

    Tabaghchi Milan S., Jafari Navimipour n.. Hybrid Method for Detecting Trustworthy Cloud Service Providers using Analytical Hierarchical Process and Neural Network. JOURNAL OF ELECTRONIC AND CYBER DEFENCE[Internet]. 2019;6(4 (24) ):105-122. Available from: https://sid.ir/paper/243141/en

    IEEE: Copy

    S. Tabaghchi Milan, and n. Jafari Navimipour, “Hybrid Method for Detecting Trustworthy Cloud Service Providers using Analytical Hierarchical Process and Neural Network,” JOURNAL OF ELECTRONIC AND CYBER DEFENCE, vol. 6, no. 4 (24) , pp. 105–122, 2019, [Online]. Available: https://sid.ir/paper/243141/en

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