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Privacy-Preserving Public Auditing and Data Dynamics for Secure Cloud Storage Based on Exact Regenerated Code
Abstract
Cloud storage allows users to store their data in the cloud to avoid local storage and management costs. Since the cloud is untrusted, the integrity of stored data in the cloud has become an issue. To address this problem, several public auditing schemes have been designed to verify integrity of the data in the cloud. However, these schemes have two drawbacks: public auditing may reveal sensitive data to verifier and does not address the data recovery problem efficiently. This article proposes a new privacy-preserving public auditing scheme with data dynamics to secure the data in the cloud based on an exact regenerated code. This scheme encodes the data for availability, then masks the encoded blocks with randomness for privacy of data and enables a public auditor to verify the integrity of the data. Further, this scheme also supports dynamic data updates. In addition, security and performance analysis proves that proposed scheme is provably secure and efficient.
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