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Achieving Data Privacy through Secrecy Views and Null-Based Virtual Updates

Published: 01 May 2013 Publication History

Abstract

We may want to keep sensitive information in a relational database hidden from a user or group thereof. We characterize sensitive data as the extensions of secrecy views. The database, before returning the answers to a query posed by a restricted user, is updated to make the secrecy views empty or a single tuple with null values. Then, a query about any of those views returns no meaningful information. Since the database is not supposed to be physically changed for this purpose, the updates are only virtual, and also minimal. Minimality makes sure that query answers, while being privacy preserving, are also maximally informative. The virtual updates are based on null values as used in the SQL standard. We provide the semantics of secrecy views, virtual updates, and secret answers (SAs) to queries. The different instances resulting from the virtually updates are specified as the models of a logic program with stable model semantics, which becomes the basis for computation of the SAs.

Cited By

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  • (2020)Specifying and computing causes for query answers in databases via database repairs and repair-programsKnowledge and Information Systems10.1007/s10115-020-01516-663:1(199-231)Online publication date: 3-Nov-2020
  • (2019)Revisiting controlled query evaluation in description logicsProceedings of the 28th International Joint Conference on Artificial Intelligence10.5555/3367243.3367286(1786-1792)Online publication date: 10-Aug-2019
  • (2019)Database Repairs and Consistent Query AnsweringProceedings of the 38th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems10.1145/3294052.3322190(48-58)Online publication date: 25-Jun-2019
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Published In

cover image IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Knowledge and Data Engineering  Volume 25, Issue 5
May 2013
238 pages

Publisher

IEEE Educational Activities Department

United States

Publication History

Published: 01 May 2013

Author Tags

  1. Data privacy
  2. answer set programs
  3. database repairs
  4. null values
  5. query answering
  6. view updates
  7. views

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Cited By

View all
  • (2020)Specifying and computing causes for query answers in databases via database repairs and repair-programsKnowledge and Information Systems10.1007/s10115-020-01516-663:1(199-231)Online publication date: 3-Nov-2020
  • (2019)Revisiting controlled query evaluation in description logicsProceedings of the 28th International Joint Conference on Artificial Intelligence10.5555/3367243.3367286(1786-1792)Online publication date: 10-Aug-2019
  • (2019)Database Repairs and Consistent Query AnsweringProceedings of the 38th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems10.1145/3294052.3322190(48-58)Online publication date: 25-Jun-2019
  • (2018)An Operational Approach to Consistent Query AnsweringProceedings of the 37th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems10.1145/3196959.3196966(239-251)Online publication date: 27-May-2018
  • (2017)First-order under-approximations of consistent query answersInternational Journal of Approximate Reasoning10.1016/j.ijar.2016.10.00583:C(337-355)Online publication date: 1-Apr-2017
  • (2017)From Causes for Database Queries to Repairs and Model-Based Diagnosis and BackTheory of Computing Systems10.1007/s00224-016-9718-961:1(191-232)Online publication date: 1-Jul-2017
  • (2015)Query-answer causality in databasesProceedings of the UAI 2015 Conference on Advances in Causal Inference - Volume 150410.5555/3020267.3020275(76-85)Online publication date: 16-Jul-2015

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