Estimating the level of authenticity and revoking misbehaving anonymous users in Cloud using FIS

Abstract

Cloud technology has become a multifaceted ecosystem, allowing for the use of resources and the effective outsourcing of access across a wide range of devices. Cloud service providers have to implement security mechanisms to identify misbehaving users. In all credential systems, cloud service provider identifies misbehaved cloud users (Irrelevant modifications to the cloud data) and categorizes them as blacklisted users without trusted third party by preserving anonymity of user.In literature, no model so far estimated thelevel of authenticity ofanonymous cloud users. This is an important measure useful for cloud service provider to take decisions depending on sensitivity of the application.The objective of the proposed method, is toprovide secure user authentication and validation of users. Secure user authentication process preserves the anonymity of the users. Validation of users includes identificationof blacklisted users and estimating the level of authenticity of the misbehaving users. Fuzzy inference system is used to validate the cloud users.The proposed technique is implemented in Cloudsim and Matlab environment.Proposed system limits the Cloud service provider’s access of sensitive applications to misbehaving users. Moreover, the results proved that the proposed method is goodat estimating the level of authenticity and revoking misbehaving anonymous users.

Keywords:Cloud Security, Cloud authentication, FuzzyInference System.