Differentially private k-skyband query answering through adaptive spatial decomposition

Ling Chen, Ting Yu, Rada Chirkova

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Given a set of multi-dimensional points, a k-skyband query retrieves those points dominated by no more than k other points. k-skyband queries are an important type of multi-criteria analysis with diverse applications in practice. In this paper, we investigate techniques to answer k-skyband queries with differential privacy. We first propose a general technique BBS-Priv, which accepts any differentially private spatial decomposition tree as input and leverages data synthesis to answer k-skyband queries privately. We then show that, though quite a few private spatial decomposition trees are proposed in the literature, they are mainly designed to answer spatial range queries. Directly integrating them with BBS-Priv would introduce too much noise to generate useful k-skyband results. To address this problem, we propose a novel spatial decomposition technique k-skyband tree specially optimized for k-skyband queries, which partitions data adaptively based on the parameter k. We further propose techniques to generate a k-skyband tree over spatial data that satisfies differential privacy, and combine BBS-Priv with the private k-skyband tree to answer k-skyband queries. We conduct extensive experiments based on two real-world datasets and three synthetic datasets that are commonly used for evaluating k-skyband queries. The results show that the proposed scheme significantly outperforms existing differentially private spatial decomposition schemes and achieves high utility when privacy budgets are properly allocated.

Original languageEnglish
Title of host publicationData and Applications Security and Privacy XXXI - 31st Annual IFIP WG 11.3 Conference, DBSec 2017, Proceedings
PublisherSpringer Verlag
Pages142-163
Number of pages22
ISBN (Print)9783319611754
DOIs
Publication statusPublished - 1 Jan 2017
Event31st Annual IFIP WG 11.3 Conference on Data and Applications Security and Privacy, DBSec 2017 - Philadelphia, United States
Duration: 19 Jul 201721 Jul 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10359 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other31st Annual IFIP WG 11.3 Conference on Data and Applications Security and Privacy, DBSec 2017
CountryUnited States
CityPhiladelphia
Period19/7/1721/7/17

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Keywords

  • Adaptive spatial decomposition
  • Differential privacy
  • K-skyband query

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Chen, L., Yu, T., & Chirkova, R. (2017). Differentially private k-skyband query answering through adaptive spatial decomposition. In Data and Applications Security and Privacy XXXI - 31st Annual IFIP WG 11.3 Conference, DBSec 2017, Proceedings (pp. 142-163). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10359 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-61176-1_8