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Abstract
Encrypted range query schemes that enable range-based searches over encrypted data have become an effective solution for secure data outsourcing services. However, existing schemes are still inadequate on desired functionality and security. Specifically, supporting efficient multi-range queries while hiding the data ordering leakage remains a challenging research problem. Existing works on order-hiding query schemes only work for encrypted single-range search and incur significant computational overhead due to the protection of the ordering information. In this paper, we present a privacy-preserving multi-range query scheme that can address the above problems simultaneously. It not only enables efficient multi-range queries over encrypted data but also guarantees the privacy of ordering information. To protect the ordering leakage, our design adopts an Order-hiding Encoding (OHE) scheme to support multi-range obfuscation. In addition, a novel order-hiding KD-tree index structure is designed as the core technique underlying our scheme, which accelerates efficient multi-range queries and obfuscates ordering information of encrypted values. Finally, the formal security analysis confirms that our proposed multi-range query scheme is secure in the random oracle model. The extensive experimental results conducted on real-world datasets demonstrate the practicality of our design.
| Original language | English |
|---|---|
| Pages (from-to) | 2431-2444 |
| Number of pages | 14 |
| Journal | IEEE Transactions on Cloud Computing |
| Volume | 11 |
| Issue number | 3 |
| Online published | 22 Sept 2022 |
| DOIs | |
| Publication status | Published - Jul 2023 |
Research Keywords
- Cloud computing
- Cryptography
- Encrypted Multi-Range Search
- Indexes
- Outsourcing
- Privacy-Preserving Data Outsourcing
- Protocols
- Remuneration
- Searchable Encryption
- Servers
Publisher's Copyright Statement
- COPYRIGHT TERMS OF DEPOSITED POSTPRINT FILE: © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Guo, Y., Xie, H., Wang, M., & Jia, X. (2022). Privacy-Preserving Multi-Range Queries for Secure Data Outsourcing Services. IEEE Transactions on Cloud Computing. https://doi.org/10.1109/TCC.2022.3208711.
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- 1 Finished
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GRF: A Blockchain-Based Federated Crowdsourcing Platform for Privacy-Preserving Applications
JIA, X. (Principal Investigator / Project Coordinator)
1/01/21 → 12/06/25
Project: Research