A multi-party protocol for privacy-preserving range queries

Maryam Sepehri, Stelvio Cimato, Ernesto Damiani

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations


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.

Original languageBritish English
Title of host publicationSecure Data Management - 10th VLDB Workshop, SDM 2013, Proceedings
PublisherSpringer Verlag
Number of pages13
ISBN (Print)9783319068107
StatePublished - 2014
Event10th VLDB Workshop on Secure Data Management, SDM 2013 - Trento, Italy
Duration: 30 Aug 201330 Aug 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8425 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference10th VLDB Workshop on Secure Data Management, SDM 2013


  • Privacy-preserving query processing and bucketization
  • Range query
  • Secure multi-party computation


Dive into the research topics of 'A multi-party protocol for privacy-preserving range queries'. Together they form a unique fingerprint.

Cite this