Development of Trust Based Access Control Models Using Fuzzy Logic in Cloud Computing

Kesarwani, Abhishek (2018) Development of Trust Based Access Control Models Using Fuzzy Logic in Cloud Computing. MTech thesis.

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Cloud computing is the technology that provides the different types of services (Saas, Paas,and IaaS) as a useful resource on the Internet. So, computing in a cloud is the popular form of Internet applications and utilized by many users. The services and resources in the cloud environment are much vulnerable to attacks and threats. In the cloud environment, resource trust value will help the cloud users to select the services of a cloud provider for processing and storing their important information. Also, service providers can give access to the users on the basis of trust value, in order to secure the cloud resources from the malicious users. Although, over the time various control access models have been proposed for secure access to the cloud environment based on cryptography, identity, and trust. In this, trust models are proposed which comes under subjective trust model based on the behavior of user and service provider to calculate the value of trust. The trust is fuzzy in nature which motivated us to apply fuzzy logic for calculating the trust values of the cloud users and
service providers in the cloud environment, this will make the more efficient environment. Parameters such as performance and elasticity are taken for trust evaluation of the resource. The attributes for calculating performance is workload and response time, for calculating elasticity we have taken scalability, availability, security, and usability. The fuzzy c-means clustering is applied on parameters for evaluating the trust value of users are bad requests, bogus requests, unauthorized requests and total requests. The proposed model is applied to a platform as a service in public cloud.

Item Type:Thesis (MTech)
Uncontrolled Keywords:Cloud Computing; Trust Models; Fuzzy Logic.
Subjects:Engineering and Technology > Computer and Information Science > Data Mining
Divisions: Engineering and Technology > Department of Computer Science Engineering
ID Code:9632
Deposited By:IR Staff BPCL
Deposited On:27 Mar 2019 17:21
Last Modified:27 Mar 2019 17:21
Supervisor(s):Khilar, Pabitra Mohan

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