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Privacy-Preserving Data Deduplication on Trusted Processors

Authors :
Hung Dang
Ee-Chien Chang
Source :
CLOUD
Publication Year :
2017
Publisher :
IEEE, 2017.

Abstract

Cloud storage providers can reduce storage costs by detecting identical files and storing only one instance of them. While appealing to the storage providers, this deduplication set-up raises various privacy concerns among clients. Various techniques to retrofit content confidentiality in deduplication have been studied in the literature. Nevertheless, data encryption alone is insufficient to protect users' privacy, for the ownership and equality information of the outsourced data left unprotected may have serious privacy implications. In this paper, we investigate a three-tier architecture that saves bandwidth otherwise incurred by server-side deduplication solutions, yet does not admit the client-side deduplication's leakage on file existence. Leveraging trusted SGX-enabled processors, we construct the first privacy-preserving data deduplication protocol that protects not only the confidentiality, but also the ownership and equality information of the outsourced data, offering better privacy guarantees in comparison with existing works on secure data deduplication. Our experiments show that the proposed protocol incurs low performance overhead over conventional solutions that provide weaker level of privacy protection.

Details

Database :
OpenAIRE
Journal :
2017 IEEE 10th International Conference on Cloud Computing (CLOUD)
Accession number :
edsair.doi...........a703461f76e6b9c4849e72388690033e