Despite of the cost effectiveness and high reliability of the cloud storage service, it has several security and privacy issues. As important as the service; it is vulnerable to attacks or outages which would bring irretrievable losses to data owners. It is a crucial requirement for the cloud service provider to provide data security practices to convince data owners that their outsourced data is available, correct and safe. Recently, many auditing schemes have been proposed to periodically verify the integrity of outsourced data in the cloud storage. However, most of these schemes audit static and single copy data files; they do not consider data dynamic operations on replicated data such as insertion, deletion and modification. Moreover, they lack the data recovery feature to repair corrupted data. This study, proposes a Multi Replica Dynamic Provable Data Possession (MR-DPDP) scheme, a public and privacy-preserving auditing scheme for replicated cloud storage which can also support efficient data recovery using Raptor codes. In addition, the proposed MR-DPDP scheme efficiently differentiates replicas by utilizing the Paillier probabilistic encryption scheme and consequently prevents cloud service providers from storing fewer replicas than have been paid for. The proposed scheme also supports efficient dynamic operations on data replicas over cloud servers. Performance analysis and experimental results prove the effectiveness and efficiency of the proposed scheme.
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