AN EXTENSIVE STUDY TOWARDS ACHIEVING FINE GRAINED ACCESS CONTROL ON ENCRYPTED CLOUD DATA

Abstract

                   Outsourcing of business, Scientific and engineering data application on the Third party administrative cloud server have been increasing from the past decade. Unfortunately many servers disregard the security requirement which entails serious security concerns. To provide Confidentiality on the shared sensitive data, many cryptographic technique are usually applied in large numbers though it has lead to serious challenges in the cloud storage against data sharing.In this paper, we study on achieving fine grained access control on encrypted cloud data against several kinds of attacks propagating to the cloud servers such as key leakage attack, Cipher text attack by deducing the key for encryption and decryption.  Fine grained access control is employed against encrypted data. In addition to more advantage, the access control mechanism also faces several issues in terms of automatic revocation. In order to handle implication of this study, we plan to propose an Ensemble operator on the Fine grained access control through Time, Location and Profile constrainst on the access policy to the attribute set defined. In this notion, expensive access policy generation for decryption of the cipher text is offloaded to the cloud to some extent. Even obtaining encryption key and decryption key, attacker will not help in decrypting the ciphertext. The proposed notion is used as key encapsulation mechanism to the data outsourced to cloud via third party application. Through extensive analysis on different fine grained access control mechanism on the outsourced data, the ensemble operator model can gain significant performance to highlight the scalability and efficiency.