Practical Attacks on Relational Databases Protected via Searchable Encryption

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceeding

Abstract

Searchable symmetric encryption (SSE) schemes are commonly proposed to enable search in a protected unstructured documents such as email archives or any set of sensitive text files. However, some SSE schemes have been recently proposed in order to protect relational databases. Most of the previous attacks on SSE schemes have only targeted its common use case, protecting unstructured data. In this work, we propose a new inference attack on relational databases protected via SSE schemes. Our inference attack enables a passive adversary with only basic knowledge about the meta-data information of the target relational database to recover the attribute names of some observed queries. This violates query privacy since the attribute name of a query is secret.

Details

Authors
Organisations
External organisations
  • Intelligent Voice Ltd.
  • RISE SICS AB
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Information Systems
Original languageEnglish
Title of host publicationInformation Security - 21st International Conference, ISC 2018, Proceedings
EditorsLiqun Chen, Mark Manulis, Steve Schneider
PublisherSpringer
Pages171-191
Number of pages21
ISBN (Print)9783319991351
Publication statusPublished - 2018
Publication categoryResearch
Peer-reviewedYes
Event21st Information Security Conference, ISC 2018 - Guildford, United Kingdom
Duration: 2018 Sep 92018 Sep 12

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11060 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference21st Information Security Conference, ISC 2018
CountryUnited Kingdom
CityGuildford
Period2018/09/092018/09/12

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Swedish Foundation for Strategic Research, SSF

2018/04/012023/03/31

Project: Other

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European Commission - Horizon 2020

2017/10/012021/03/31

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