Cooperative Provable Data possession for integrity verification in multicloud
Shriniwas Gadage · 2015
To ensure the integrity of data in storage outsourcing Provable data possession (PDP) is a technique. In this paper, there is the construction of an efficient PDP scheme for distributed cloud storage to support the scalability of service and data migration, where the existence of multiple cloud service providers to cooperatively store and maintain the client's data. This paper presents a cooperative PDP (CPDP) scheme based on homomorphic verifiable response and hash index hierarchy. In this paper proof of the security of CPDP scheme based on multi-prover zero-knowledge proof system, which can satisfy completeness, knowledge soundness, and zero-knowledge properties, is given. To provide a low-cost, scalable, location independent platform for managing clients' data, current cloud storage systems adopt several new distributed file systems, Apache HDFS, GFS, Amazon S3 File System, CloudStore etc. These file systems share some similar features: a single metadata server provides centralized management by a global namespace; files are split into blocks or chunks and stored on block servers; and the systems are comprised of interconnected clusters of block servers. Those features enable cloud service providers to store and process large amounts of data. It is crucial to offer an efficient verification on the integrity and availability of stored data for detecting faults and automatic recovery. Moreover, this verification is necessary to provide reliability by automatically maintaining multiple copies of data and automatically redeploying processing logic in the event of failures. Although existing schemes can make a false or true decision for data possession without downloading data at untrusted stores, and are not suitable for a distributed cloud storage environment as they were not originally constructed on interactive proof system. They use an authenticated skip list to check the integrity of file blocks adjacently in space. They did not provide any algorithms for constructing distributed Merkle trees that are necessary for efficient verification in a multi-cloud environment. When a client asks for a file block, the server needs to send the file block along with a proof for the intactness of the block. This process incurs significant communication overhead in a multi-cloud environment, since the server in one cloud typically needs to generate such a proof with the help of other cloud storage services, where the adjacent blocks are stored. The schemes PDP (2), CPOR-I (5), and CPOR-II (6) are constructed on homomorphic verification tags by which the server can generate tags for multiple file blocks in terms of a single response value. However, that doesn't mean the responses from multiple clouds can be also combined into a single value on the client side. For lack of homomorphic responses, clients must invoke the PDP protocol repeatedly to check the integrity of file blocks stored in multiple clouds servers. Also, clients need to know the exact position of each file block in a multi-cloud environment. In addition, the verification process in such a case will lead to high communication overheads and computation costs at client sides as well. Therefore, it is of utmost necessary to design a cooperative PDP model to reduce the storage and network overheads and enhance the transparency of verification activities in cluster-based cloud storage