Constrained anonymization of production data: A constraint satisfaction problem approach

Ran Yahalom, Erez Shmueli, Tomer Zrihen

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

9 Scopus citations


The use of production data which contains sensitive information in application testing requires that the production data be anonymized first. The task of anonymizing production data becomes difficult since it usually consists of constraints which must also be satisfied in the anonymized data. We propose a novel approach to anonymize constrained production data based on the concept of constraint satisfaction problems. Due to the generality of the constraint satisfaction framework, our approach can support a wide variety of mandatory integrity constraints as well as constraints which ensure the similarity of the anonymized data to the production data. Our approach decomposes the constrained anonymization problem into independent sub-problems which can be represented and solved as constraint satisfaction problems (CSPs). Since production databases may contain many records that are associated by vertical constraints, the resulting CSPs may become very large. Such CSPs are further decomposed into dependant sub-problems that are solved iteratively by applying local modifications to the production data. Simulations on synthetic production databases demonstrate the feasibility of our method.

Original languageEnglish
Title of host publicationSecure Data Management - 7th VLDB Workshop, SDM 2010, Proceedings
PublisherSpringer Verlag
Number of pages13
ISBN (Print)3642155456, 9783642155451
StatePublished - 1 Jan 2010
Event7th VLDB Workshop on Secure Data Management, SDM 2010 - Singapore, Singapore
Duration: 17 Sep 201017 Sep 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6358 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference7th VLDB Workshop on Secure Data Management, SDM 2010

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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