Journal
2020 IEEE 19TH INTERNATIONAL CONFERENCE ON TRUST, SECURITY AND PRIVACY IN COMPUTING AND COMMUNICATIONS (TRUSTCOM 2020)
Volume -, Issue -, Pages 639-645Publisher
IEEE COMPUTER SOC
DOI: 10.1109/TrustCom50675.2020.00090
Keywords
spatial data; cloud server; circular range search; index privacy; query privacy
Categories
Funding
- National Natural Science Foundation of China [61632012, 61672239]
- Peng Cheng Laboratory Project of Guangdong Province [PCL2018KP004]
- Fundamental Research Funds for the Central Universities
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With the location-based services (LBS) booming, the volume of spatial data inevitably explodes. In order to reduce local storage and computational overhead, users tend to outsource data and initiate queries to the cloud. However, sensitive data or queries may be compromised if cloud server has access to raw data and plaintext token. To cope with this problem, searchable encryption for geometric range is applied. Geometric range search has wide applications in many scenarios, especially the circular range search. In this paper, a practical and secure circular range search scheme (PSCS) is proposed to support searching for spatial data in a circular range. With our scheme, a semi-honest cloud server will return data for a given circular range correctly without uncovering index privacy or query privacy. We propose a polynomial split algorithm which can decompose the inner product calculation neatly. Then, we define the security of our PSCS formally and prove that it is secure under same-closeness-pattern chosen-plaintext attacks (CLS-CPA) in theory. In addition, we demonstrate the efficiency and accuracy through analysis and experiments compared with existing schemes.
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