Privacy Preserving Dynamic Provable Data Possession with Batch Update for Secure Cloud Storage

Abstract

Cloud Server (CS) is an untrusted entity in cloud paradigm that may hide accidental data loss to maintain its reputation. Provable Data Possession (PDP) is a model that allows Third Party Auditor (TPA) to verify the integrity of outsourced data on behalf of cloud user without downloading the data files. But this public auditing model faces many security and performance issues such as: unnecessary computational burden on user as well as on TPA, to preserve identities of users from TPA during auditing, support for dynamic updates etc. Many PDP schemes creates computational burden either on TPA or Cloud User. To balance this overhead between TPA and User, this paper proposes Privacy-Preserving Dynamic Provable Data Possession (P2DPDP) scheme, which is based on ODPDP scheme. In ODPDP scheme, user relieves the burden by signing a contract with TPA regarding verification of his outsourced data. But this scheme generates computation overhead on TPA. To reduce this computation overhead of TPA, our P2DPDP scheme uses Indistinguishability Obfuscation (IO) with one-way function such as message authentication code to make a lightweight auditing process. P2DPDP scheme uses Rank-based Merkle Tree (RBMT) to support dynamic updates in batch mode which greatly reduces computation overhead of TPA. ODPDP lacks privacy which is maintained in P2DPDP using ring signature technique. Our experimental results demonstrate the reduced verification time and computation cost compared to existing schemes.