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2018 IEEE 34th International Conference on Data Engineering (ICDE) (2018)
Paris, France
Apr 16, 2018 to Apr 19, 2018
ISSN: 2375-026X
ISBN: 978-1-5386-5520-7
pp: 857-868
Performing non-aggregate range queries on cloud stored data, while achieving both privacy and efficiency is a challenging problem. This paper proposes constructing a differentially private index to an outsourced encrypted dataset. Efficiency is enabled by using a cleartext index structure to perform range queries. Security relies on both differential privacy (of the index) and semantic security (of the encrypted dataset). Our solution, PINED-RQ develops algorithms for building and updating the differentially private index. Compared to state-of-the-art secure index based range query processing approaches, PINED-RQ executes queries in the order of at least one magnitude faster. The security of PINED-RQ is proved and its efficiency is assessed by an extensive experimental validation.
cloud computing, cryptography, data privacy, query processing

C. Sahin, T. Allard, R. Akbarinia, A. El Abbadi and E. Pacitti, "A Differentially Private Index for Range Query Processing in Clouds," 2018 IEEE 34th International Conference on Data Engineering (ICDE), Paris, France, 2018, pp. 857-868.
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