A method for trust evaluation in the cloud environments using a behavior graph and services grouping. Issue 7 (7th August 2017)

• Record Type: Journal Article
• Authors: Hajizadeh, Roghiyeh; Jafari Navimipour, Nima
• Is Part Of: Kybernetes. Volume 46:Issue 7(2017)
• Page Start: 1245
• Page End: 1261
• Publication Date: 2017-08-07
• Subjects: Trust -- Cloud services -- Behavioral graph -- Grouping of service; Cybernetics -- Periodicals; Systems engineering -- Periodicals; 003.505
• DOI: 10.1108/K-02-2017-0070
• Languages: English
• ISSNs: 0368-492X

Abstract

Abstract : Purpose: Cloud services have become very popular among researchers and people recently. In such a scenario, identifying reliable cloud services has become very important. The trust value plays a significant role in recognizing reliable providers. The purpose of this paper is to propose a new method to evaluate the trust metric among the cloud providers. The main goal is to increase the precision and accuracy of the trust evaluation method in the cloud environments. Design/methodology/approach: This paper evaluates the trust metric among the cloud providers and entities by grouping the services and using a behavioral graph. Four parameters, availability, reliability, interaction evolution and identity, are used for evaluating the trust value. The performance of the proposed method is assessed using a simulator which is programmed in the cloud Azure 2013 based on C# codes. Findings: The method is evaluated through various experiments in terms of precision, recall, error-hit, reliability and availability. The obtained results show that the proposed method has better reliability and availability than the FIFO and QoS models. Also, the results show that increasing the number of groups leads to increasing values of trust, precision and availability, and decreasing values of error-hit. Originality/value: This paper proposes a trust evaluation method in the cloud environment by grouping the services and using a behavioral graph for improving the amount of availability, error-hit, precision and reliability values.