Privacy-preserving two-party skyline queries over horizontally partitioned data

Ling Chen*, Ting Yu, Rada Chirkova

*Corresponding author for this work

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

Abstract

Skyline queries are an important type of multi-criteria analysis with diverse applications in practice (e.g., personalized services and intelligent transport systems). In this paper, we study how to answer skyline queries efficiently and in a privacy-preserving way when the data are sensitive and distributedly owned by multiple parties. We adopt the classical honest-but-curious attack model, and design a suite of efficient protocols for skyline queries over horizontally partitioned data. We analyze in detail the efficiency of each of the proposed protocols as well as their privacy guarantees.

Original languageEnglish
Title of host publicationInformation Security Theory and Practice - 10th IFIP WG 11.2 International Conference, WISTP 2016, Proceedings
EditorsSara Foresti, Javier Lopez
PublisherSpringer Verlag
Pages187-203
Number of pages17
ISBN (Print)9783319459301
DOIs
Publication statusPublished - 2016
Event10th IFIP WG 11.2 International Conference on Information Security Theory and Practice, WISTP 2016 - Heraklion, Crete, Greece
Duration: 26 Sept 201627 Sept 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9895 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th IFIP WG 11.2 International Conference on Information Security Theory and Practice, WISTP 2016
Country/TerritoryGreece
CityHeraklion, Crete
Period26/09/1627/09/16

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