Trust in Cloud: Perspective from Access Control Models and Machine Learning-A Detailed Study

Abstract

The number of cloud users and the cloud service providers are in increasing trend. With the concepts that allow the users to login to various services with a single identity, it is mandatory to check the trustworthiness of the users as well the service providers. So it is obvious any access made should be trusted at both the ends in the cloud environment. When a study is made on the trust evaluation models, it is observed that most of the models are dependent on the past behavior of the entity concerned. This depicts the suitability of the machine learning model in evaluating trust in the trust based access control models. To have a clear understanding a study is made on the various works in three contexts. First, Access control models employed in the cloud location, RBAC (Role Based Access Control), ABAC (Attribute Based Access Control) and in detail Trust based access control model. Second the usage of machine learning models in the context of addressing various security issues in the cloud computing and in the context of usage of machine learning models in access control models. Third various Trust evaluation techniques that are in practice in the cloud environment is also studied. The inferences made from the studies are also discussed.