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A Survey of Query Auditing Techniques for Data Privacy

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Privacy-Preserving Data Mining

Part of the book series: Advances in Database Systems ((ADBS,volume 34))

This chapter is a survey of query auditing techniques for detecting and preventing disclosures in a database containing private data. Informally, auditing is the process of examining past actions to check whether they were in conformance with official policies. In the context of database systems with specific data disclosure policies, auditing is the process of examining queries that were answered in the past to determine whether answers to these queries could have been used by an individual to ascertain confidential information forbidden by the disclosure policies. Techniques used for detecting disclosures could potentially also be used or extended to prevent disclosures, and so in addition to the retroactive auditing mentioned above, researchers have also studied an online variant of the auditing problem wherein the task of an online auditor is to deny queries that could potentially cause a breach of privacy.

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References

  1. N. Adam and J. Wortmann. Security-control methods for statistical databases: a comparative study. ACM Computing Surveys, 21(4):515–556, 1989.

    Article  Google Scholar 

  2. R. Agrawal, R. Bayardo, C. Faloutsos, J. Kieman, R. Rantzau, and R. Srikant. Auditing Compliance with a Hippocratic Database. In Proceedings of the International Conference on Very Large Databases (VLDB), 2004.

    Google Scholar 

  3. D. Applegate and R. Kannan. Sampling and integration of near log-concave functions. In Proceedings of the ACM Symposium on Theory of Computing (STOC), pages 156–163, 1991.

    Google Scholar 

  4. F. Chin. Security Problems on Inference Control for SUM, MAX, and MIN Queries. J. ACM, 33(3):451–464, 1986.

    Article  MathSciNet  Google Scholar 

  5. N. Dalvi, G. Miklau, and D. Suciu. Asymptotic Conditional Probabilities for Conjunctive Queries. In Proceedings of the International Conference on Database Theory (ICDT), 2007.

    Google Scholar 

  6. D. Dobkin, A. Jones, and R. Lipton. Secure Databases: Protection against User Influence. ACM Transactions on Database Systems (TODS), 4(1):97–106, 1979.

    Article  Google Scholar 

  7. A. Frieze and R. Kannan. Log-sobolev inequalities and sampling from log-concave distributions. Annals of Applied Probability, 9(1):14–26, February 1999.

    Article  MATH  MathSciNet  Google Scholar 

  8. J. Kam and J. Ullman. A model of statistical databases and their security. ACM Transactions on Database Systems (TODS), 2(1):1–10, 1977.

    Article  Google Scholar 

  9. R. Kannan, L. Lovasz, and M. Simonovits. Random walks and an O ∗(n 5) volume algorithm for convex bodies. Random Structures and Algorithms, 11, 1997.

    Google Scholar 

  10. K. Kenthapadi. Models and Algorithms for Data Privacy. Ph.D. Thesis, Computer Science Department, Stanford University, 2006.

    Google Scholar 

  11. K. Kenthapadi, N. Mishra, and K. Nissim. Simulatable Auditing. In Proceedings of the ACM Symposium on Principles of Database Systems (PODS), pages 118–127, 2005.

    Google Scholar 

  12. J. Kleinberg, C. Papadimitriou, and P. Raghavan. Auditing Boolean Attributes. Journal of Computer and System Sciences, 6:244–253, 2003.

    Article  MathSciNet  Google Scholar 

  13. L. Lovasz and S. Vempala. Logconcave functions: Geometry and efficient sampling algorithms. In Proceedings of the IEEE Symposium on Foundations of Computer Science (FOCS), 2003.

    Google Scholar 

  14. L. Lovasz and S. Vempala. Simulated annealing in convex bodies and an O ∗(n 4) volume algorithm. In Proceedings of the IEEE Symposium on Foundations of Computer Science (FOCS), pages 650–659, 2003.

    Google Scholar 

  15. A. Machanavajjhala and J. Gehrke. On the Efficiency of Checking Perfect Privacy. In Proceedings of the ACM Symposium on Principles of Database Systems (PODS), 2006.

    Google Scholar 

  16. G. Miklau and D. Suciu. A Formal Analysis of Information Disclosure in Data Exchange. Journal of Computer and System Sciences, 2006.

    Google Scholar 

  17. R. Motwani, S. U. Nabar, and D. Thomas. Auditing SQL Queries. In Proceedings of the International Conference on Data Engineering (ICDE), 2008.

    Google Scholar 

  18. S. U. Nabar, B. Marthi, K. Kenthapadi, N. Mishra, and R. Motwani. Towards Robustness in Query Auditing. In Proceedings of the International Conference on Very Large Databases (VLDB), 2006.

    Google Scholar 

  19. S. Reiss. Security in Databases: A Combinatorial Study. J. ACM, 26(1):45–57, 1979.

    Article  MATH  MathSciNet  Google Scholar 

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Nabar, S.U., Kenthapadi, K., Mishra, N., Motwani, R. (2008). A Survey of Query Auditing Techniques for Data Privacy. In: Aggarwal, C.C., Yu, P.S. (eds) Privacy-Preserving Data Mining. Advances in Database Systems, vol 34. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-70992-5_17

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  • DOI: https://doi.org/10.1007/978-0-387-70992-5_17

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-0-387-70991-8

  • Online ISBN: 978-0-387-70992-5

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