Privacy-preserving query processing (PPQP) techniques are increasingly important in collaborative scenarios, where users need to execute queries on large amount of data shared among different parties who do not want to disclose private data to the others. In many cases, secure multi-party computation (SMC) protocols can be applied, but the resulting solutions are known to suffer from high computation and communication costs. In this paper, we describe a scalable protocol for performing queries in distributed data while respecting the data owners' privacy. Our solution is applicable both to equality and range queries, and relies on a bucketization technique in order to reduce time complexity. We show the effectiveness of our approach through theoretical and practical analysis.

A multi-party protocol for privacy-preserving range queries / M. Sepehri, S. Cimato, E. Damiani (LECTURE NOTES IN COMPUTER SCIENCE). - In: Secure Data Management / [a cura di] W. Jonker, M. Petković. - [s.l] : Springer Verlag, 2014. - ISBN 9783319068107. - pp. 108-120 (( Intervento presentato al 10. convegno VLDB tenutosi a Trento nel 2013 [10.1007/978-3-319-06811-4_15].

A multi-party protocol for privacy-preserving range queries

M. Sepehri
;
S. Cimato
Secondo
;
E. Damiani
Ultimo
2014

Abstract

Privacy-preserving query processing (PPQP) techniques are increasingly important in collaborative scenarios, where users need to execute queries on large amount of data shared among different parties who do not want to disclose private data to the others. In many cases, secure multi-party computation (SMC) protocols can be applied, but the resulting solutions are known to suffer from high computation and communication costs. In this paper, we describe a scalable protocol for performing queries in distributed data while respecting the data owners' privacy. Our solution is applicable both to equality and range queries, and relies on a bucketization technique in order to reduce time complexity. We show the effectiveness of our approach through theoretical and practical analysis.
Privacy-preserving query processing and bucketization; Range query; Secure multi-party computation
Settore INF/01 - Informatica
2014
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/417219
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