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Searchable symmetric encryption: Improved definitions and efficient constructions

Curtmola, Reza, Garay, Juan, Kamara, Seny, Ostrovsky, Rafail·2011·Journal of Computer Security

Abstract

Searchable symmetric encryption (SSE) allows a party to outsource the storage of his data to another party in a private manner, while maintaining the ability to selectively search over it. This problem has been the focus of active research and several security definitions and constructions have been proposed. In this paper we begin by reviewing existing notions of security and propose new and stronger security definitions. We then present two constructions that we show secure under our new definitions. Interestingly, in addition to satisfying stronger security guarantees, our constructions are more efficient than all previous constructions. Further, prior work on SSE only considered the setting where only the owner of the data is capable of submitting search queries. We consider the natural extension where an arbitrary group of parties other than the owner can submit search queries. We formally define SSE in this multi-user setting, and present an efficient construction.

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Metadata

Authors
Curtmola, R., Garay, J., Kamara, S., & Ostrovsky, R.
Venue
Journal of Computer Security
Published
2011-11-04
Volume
19
Issue
5
Pages
895-934
ISSN
  • 0926-227X (ISSN-L)
  • 1875-8924
OpenAlex
W2145426052
Cited by
914
References
26
FWCI
18.92
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Searchable symmetric encryption: Improved definitions and efficient constructions. https://app.cochat.ai/papers/10.3233/jcs-2011-0426
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Curtmola, R., Garay, J., Kamara, S., & Ostrovsky, R. (2011). Searchable symmetric encryption: Improved definitions and efficient constructions. Journal of Computer Security. https://doi.org/10.3233/jcs-2011-0426

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.