A Novel Data Deduplication Scheme for Encrypted Cloud Databases

Jung-Shian Li,
I-Hsien Liu,
Chao-Yuan Lee,
Chu-Fen Li,
Chuan-Gang Liu,


As the demand for data sharing and complex access-control policies continues to grow, traditional encryption mechanisms, which are generally established using a Public Key Infrastructure, face the problem of massive processing overheads and huge network bandwidth consumption. Attribute-Based Encryption (ABE) schemes have been proposed as a potential means of addressing these issues and have attracted great attention in recent years. Most previous studies on ABE focus on issues such as the revocation mechanism, multi-authority, the access structure design, and traceability. However, very few studies consider the storage efficiency problem and the present study proposes a novel data deduplication scheme based on ciphertext-policy ABE with convergent encryption and block-level data. The scheme can be deployed in third-party semi-trusted environments, and not only provides flexible, fine-grained access control over encrypted data, but also allows for the in-line elimination of redundancies in order to save cloud storage space. The experimental results show that the proposed scheme has an acceptable computational overhead and provides a promising solution for real-world data cloud storage and access scenarios.

Citation Format:
Jung-Shian Li, I-Hsien Liu, Chao-Yuan Lee, Chu-Fen Li, Chuan-Gang Liu, "A Novel Data Deduplication Scheme for Encrypted Cloud Databases," Journal of Internet Technology, vol. 21, no. 4 , pp. 1115-1125, Jul. 2020.

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