JISE

    As the era of big data is coming, more and more users choose to store data in the cloud. Cloud storage provides users with flexible, dynamic and cost effective data storage service. However, the new paradigm of service introduces new security challenges such as users loss control of the remote data and they cannot ensure data integrity in the cloud. Moreover, supporting dynamic data updates is also a practical requirement of cloud storage. It is imperative to provide an efficient and secure dynamic auditing protocol to check the data integrity in the cloud. In this paper, we first analyze the dynamic performance of some prior works. In order to solve the inefficiency problem caused by the Merkle Hash Tree (MHT) in dynamic update, the Large Branching Tree (LBT) data structure was introduced in our Dynamic Provable Data Possession (DPDP) scheme. LBT structure simplifies the process of updates and supports updating several blocks synchronously, and reduces the auxiliary information during the challenge-respond process as well. Our scheme is able to efficiently support fully dynamic data updates and batch updates. Based on the LBT structure, we use bilinear algebraic maps to optimize the authenticate process. A signature scheme is used to authenticate both the value and the position of data blocks, which reduces computation overhead during the dynamic update phase. The security and performance analysis show that our DPDP scheme is provably secure and efficient.