Abstract
In this paper, we propose a new heuristic algorithm called the QIBC algorithm that improves the privacy of sensitive knowledge (as itemsets) by blocking more inference channels. We show that the existing sanitizing algorithms for such task have fundamental drawbacks. We show that previous methods remove more knowledge than necessary for unjustified reasons or heuristically attempt to remove the minimum frequent non-sensitive knowledge but leave open inference channels that lead to discovery of hidden sensitive knowledge. We formalize the refined problem and prove it is NP-hard. Finally, experimental results show the practicality of the new QIBC algorithm.
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Agrawal, R., Imielinski, T., Swami, A.: Mining association rules between sets of items in large databases. In: Proc. of the ACM SIGMOD Conference on Management of Data, Washington D.C, USA, May 1993, pp. 207–216 (1993)
Atallah, M., Bertino, E., Elmagarmid, A., Ibrahim, M., Verykios, V.: Disclosure limitation of sensitive rules. In: Proc. of 1999 IEEE Knowledge and Data Engineering Exchange Workshop (KDEX 1999), Chicago, IL, November 1999, pp. 45–52 (1999)
Brijs, T., Swinnen, G., Vanhoof, K., Wets, G.: Using association rules for product assortment decisions: a case study. In: Knowledge Discovery and Data Mining, pp. 254–260 (1999)
Clifton, C., Kantarcioglu, M., Vaidya, J.: Defining privacy for data mining. In: Proc. of the National Science Foundation Workshop on Next Generation Data Mining, Baltimore, MD, USA, November 2002, pp. 126–133 (2002)
Farkas, C., Jajodia, S.: The inference problem: a survey. In: Proc. of the ACM SIGKDD Explorations Newsletter, New York, NY, USA, vol. 4, pp. 6–11. ACM Press, New York (2002)
Han, J.M.: Data Mining: Concepts and Techniques (2001)
Lindell, Y., Pinkas, B.: Privacy preserving data mining. In: Bellare, M. (ed.) Proceedings of CRYPTO 2000 Advances in Cyptology, Santa Barbara, California, USA, August 20-24, pp. 36–54 (2000)
Oliveira, S.R.M., Zaïane, O.R., Saygın, Y.: Secure association rule sharing. In: Dai, H., Srikant, R., Zhang, C. (eds.) PAKDD 2004. LNCS (LNAI), vol. 3056, pp. 74–85. Springer, Heidelberg (2004)
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HajYasien, A., Estivill-Castro, V., Topor, R. (2006). Sanitization of Databases for Refined Privacy Trade-Offs. In: Mehrotra, S., Zeng, D.D., Chen, H., Thuraisingham, B., Wang, FY. (eds) Intelligence and Security Informatics. ISI 2006. Lecture Notes in Computer Science, vol 3975. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760146_51
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DOI: https://doi.org/10.1007/11760146_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34478-0
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