Identity-Based Batch Provable Data Possession with Detailed Analyses

Abstract

In the era of big data, cloud storages become prevalent while security issues on outsourced data emerge. Without the physical control of the data owners, the outsourced data faces more risks. Provable Data Possession (PDP) is a probabilistic technique for checking whether data is correctly stored in remote servers without retrieving the entire data. For many previous PDP schemes, correctly choosing public keys for data owners relies on the security of Public Key Infrastructure (PKI), which is resource consuming. In this paper, we propose an Identity-Based Batch Provable Data Possession (ID-BPDP) scheme to eliminate the certificate management. Meanwhile, to the best of our knowledge, it is the first identity-based provable data possession scheme supporting batch verification for multiple owners and multiple clouds simultaneously to reduce computation cost greatly. We prove that our scheme is correct and secure based on bilinear pairings and the hardness assumption of Computational Diffie-Hellman problem, and also give detailed analyses to show that our scheme is able to verify the integrity of data efficiently.