Public Cloud Data for Auditable Access Control using De-Duplication Technique

In public cloud storage system protecting the data and controlling the data access is a challenging issue. Cipher text Policy Attribute-Based Encryption (CP-ABE) has been adopted as a promising technique to provide flexible, fine-grained and secure data access control for cloud storage with honest-but-curious cloud servers. However numerous works have been proposed using CP-ABE scheme, in which the single attribute authority must execute the time-consuming user legitimacy verification and secret key distribution and hence it results in a single-point performance bottleneck when a CP-ABE scheme is adopted in a large-scale cloud storage system. Clients may be stuck in the waiting line for a long stretch to get their mystery keys, which results in low-efficiency of the framework. Even though the multi authority access control plans have been proposed, these plans still cannot conquer the disadvantages of single-point bottleneck and low efficiency; because of the way that each of the authority still autonomously deals with a disjoint characteristic set. In order to overcome this disadvantage, there has been proposed a novel heterogeneous framework to remove the problem of single point performance bottleneck and provide a more efficient access control scheme with an auditing mechanism. This framework employs multiple attribute authorities to share the load of user legitimacy verification. Meanwhile, in this scheme, a CA (Central Authority) is introduced to generate secret keys for legitimacy verified users and each of the authorities in this scheme manages the whole attribute set individually. This system makes performance improvement in key generation and also guarantees security requirement. Still there are some security loopholes in this system such as there is no protocol to verify owner and if the owner is compromised then he/she may put wrong data or information in the data server and users may get wrong data. There is no way to know who has used the data.