Public auditing for shared cloud data with efficient and secure group management

With increasing popularity of collaboration in clouds, shared data auditing has become an important issue in cloud auditing field, and attracted extensive attention from the research community. However, none of the state of the arts can fully achieve all indispensable functional and security requirements. Thus, in this paper, we present a comprehensive public auditing scheme for shared data. Specifically, to preserve users' identity privacy, signatures on the challenged blocks are converted to the ones signed by the group manager during proof generation; to protect data privacy, a random masking is adopted to blind data proof; a modification record table is designed to record operation information to support identity traceability; we further extend the dynamic hash table to support shared-data dynamics, and present a batch auditing strategy. Moreover, we design a lazy-revocation based group management mechanism to achieve efficient group dynamics, which can resist collusion attacks while significantly reducing computational costs. We formally prove the security of our scheme, and evaluate its performance by comprehensive experiments and comparisons with the state-of-the-art ones. The results demonstrate that our scheme can effectively achieve secure auditing and outperforms the previous ones in computational overhead while maintaining relatively low communication costs.