Efficient Multi-Replica Cloud Data Integrity Checking Method Based on Enhanced PRF

Abstract

Cloud storage is vital nowadays due to its scalability and availability. Clients can save their information on cloud without sustaining a local replica. To maintain privacy, the owners can confirm the integrity of the outsourced information. Users allow third-party auditors to prove the honesty of the data saved on the cloud server. Data integrity checking, plays a crucial role in safeguarding the user’s data, particularly when kept in public clouds such as Microsoft Azure. To ensure the availability of stored data, users prefer multiple copies of data at multiple locations. Honesty checking of multiple copies can also be guaranteed with integrity checking techniques. Even though various scholars have proposed several multi-replica truthfulness checking schemes, many possess computational overhead during honesty verification. In this paper, an enhanced puncturable pseudorandom function is proposed to bring down the third-party auditor’s processing overhead, as well as the cloud server during proof verification and proof generation of replica data blocks. The scheme supports dynamic updating of stored data in the cloud server with less communication overhead for insertion/modification and deletion. An indistinguishability obfuscation-based program is also used to preserve the confidentiality of the data stored.