Development of trust based access control models using fuzzy logic in cloud computing

TL;DR

This paper proposes a fuzzy logic-based trust model for cloud computing that evaluates trustworthiness of users and providers using performance and elasticity parameters, enhancing security and resource allocation.

Contribution

It introduces a novel fuzzy trust model utilizing Mamdani fuzzy inference and fuzzy C-means clustering for trust evaluation in cloud environments.

Findings

Fuzzy trust evaluation improves security in cloud services.

The model effectively distinguishes trustworthy users and providers.

Application of Mamdani fuzzy logic enhances trust calculation accuracy.

Abstract

Cloud computing is the technology that provides different types of services as a useful resource on the Internet. Resource trust value will help the cloud users to select the services of a cloud provider for processing and storing their essential information. Also, service providers can give access to users based on trust value to secure cloud resources from malicious users. In this paper, trust models are proposed, which comes under the subjective trust model based on the behavior of user and service provider to calculate the trust values. The trust is fuzzy, which motivated us to apply fuzzy logic for calculating the trust values of the cloud users and service providers in the cloud environment. We use a Mamdani fuzzy method with gauss membership function for fuzzification and triangular membership function for defuzzification. Parameters such as performance and elasticity are taken for trust evaluation of the resource. The attributes for calculating performance are workload and response time. And for calculating elasticity, we have taken scalability, availability, security, and usability. The fuzzy C-means clustering is applied to parameters for evaluating the trust value of users such as bad requests, bogus requests, unauthorized requests, and total requests.