A Dynamic Weighted Averaging Technique for Trust Assessment in Cloud Computing

Abstract

In the Cloud computing, trust management has become a key requirement for its security as it has an important role where service-interactions take place in an anonymous environment. Trust assessment is an essential part of trust management technology for making any authorization decisions in the Cloud-based trust authorization system. The critical concern in trust assessment is the optimal assignment of weights to different factors that are involved in the trust assessment of the Cloud computing. The paper proposes a weighted averaging method for the Cloud computing paradigm wherein multiple factors are assigned weights dynamically by WMA-OWA functions. The proposed work overcomes the influence of the inflexibility of subjective weight assignment methods wherein weights are assigned manually or subjectively by experts based on their preferences such as random allocation, expert opinion, and, average weight. The experimental result shows that the proposed method can achieve greater flexibility, adaptability, and dynamic adjustment capability in the Cloud computing.

Fuzzy Decision Support Systems for Selection of NEA Detection Technologies Under Non-Linear Diophantine Fuzzy Hamacher Aggregation Information

“…With this aim, we shall apply a novel combination of MADM with the N-LDF approach to the context of Hamacher operators. Many researchers have recently made interesting case study related to their work which improved the research field and give us rich knowledge some of them is cited as [14]- [18]. Literature Review:…”