Aggregated privacy-preserving auditing for cloud data integrity - Kai HE; Chuan-he HUANG; Xiao-mao WANG; Jing WANG; Jiao-li SHI (Tongxin xuebao)
To solve the problem of data integrity in cloud storage,an aggregated privacy-preserving auditing scheme was proposed.To preserve data privacy against the auditor,data proof and tag proof were encrypted and combined by using the bilinearity property of the bilinear pairing on the cloud server.Furthermore,an efficient index mechanism was designed to support dynamic auditing,which could ensure that data update operations did not lead to high additional computation or communication cost.Meanwhile,an aggregation method for different proofs was designed to handle multiple auditing requests.Thus the proposed scheme could also support batch auditing for multiple owners and multiple clouds and multiple files.The communication cost of batch auditing was independent of the number of auditing requests.The theoretical analysis and experimental results show that the proposed scheme is provably secure.Compared with existing auditing scheme,the efficacy of the proposed individual auditing and batch auditing improves 21.5% and 31.8% respectively.