Privacy-Preserving Deduplication and Data Integrity Auditing for Compressed Cloud Storage

Integrating data deduplication with integrity auditing offers a practical approach to reducing cloud storage cost while safeguarding the integrity of outsourced data. Most of the existing schemes attempt to further reduce storage cost by performing authenticator deduplication on top of data deduplication. However, these schemes still require users to produce and upload the authenticators to the cloud for integrity verification. The generation of authenticators typically relies on BLS signature, which involves numerous costly exponentiation operations and requires bilinear pairing operations for verification. Moreover, most of these schemes risk leaking user file ownership information during the auditing process. In this paper, we propose a privacy-preserving deduplication and data integrity auditing scheme for compressed cloud storage. We design a novel encryption strategy wherein the users only perform lightweight algebraic operations to generate the file ciphertext. Based on this ciphertext, our scheme not only achieves data deduplication but also enables data integrity verification without relying on traditional authenticators, thereby significantly reducing storage and communication costs. In addition, we employ a randomized blinding technique to blind the file tag, auditing proof, and users’ public keys, effectively preventing the third-party auditor from inferring file ownership. Finally, we present comprehensive security analysis and experimental results to validate the security and efficiency of our scheme. Experimental results show that, compared with prior schemes, our scheme significantly reduces the computation cost in the initial upload phase, achieving up to a 2250-fold reduction. This improvement mainly stems from the use of lightweight algebraic operations. Furthermore, the proof generation process is accelerated by approximately 1480-fold, while the storage cost is reduced by up to 52%.