A TRADEOFF BALANCING ALGORITHM FOR HIDING SENSITIVE FREQUENT ITEMSETS

Harun Gökçe, Osman Abul

Abstract

Sensitive frequent itemset hiding problem is typically solved by applying a sanitization process which transforms the source database into a release version. The main challenge in the process is to preserve the database utility while ensuring no sensitive knowledge is disclosed, directly or indirectly. Several algorithmic solutions based on different approaches are proposed to solve the problem. We observe that the available algorithms are like seesaws as far as both effectiveness and efficiency performances are considered. However, most practical domains demand for solutions with satisfactory effectiveness/efficiency performances, i.e., solutions balancing the tradeoff between the two. Motivated from this observation, in this paper, we present yet a simple and practical frequent itemset hiding algorithm targeting the balanced solutions. Experimental evaluation, on two datasets, shows that the algorithm indeed achieves a good balance between the two performance criteria.

References

  1. Abul, O., Atzori, M., Bonchi, F., and Giannotti, F. (2007a). Hiding sensitive trajectory patterns. In 6th Int. Workshop on Privacy Aspects of Data Mining (PADM'07).
  2. Abul, O., Atzori, M., Bonchi, F., and Giannotti, F. (2007b). Hiding sequences. In Third ICDE Int. Workshop on Privacy Data Management (PDM'07).
  3. Abul, O., Gökc¸e, H., and S¸engez, Y. (2009). Frequent itemsets hiding: A performance evaluation framework. In ISCIS'09.
  4. Agrawal, R., Imielienski, T., and Swami, A. (1993). Mining association rules between sets of items in large databases. In SIGMOD 7893, pages 207-216.
  5. Atallah, M., Bertino, E., Elmagarmid, A., Ibrahim, M., and Verykios, V. S. (1999). Disclosure limitation of sensitive rules. In KDEX'99, pages 45-52.
  6. Brijs, T., Swinnen, G., Vanhoof, K., and Wets, G. (1999). Using association rules for product assortment decisions: A case study. In Knowledge Discovery and Data Mining, pages 254-260.
  7. Lee, G., Chang, C.-Y., and Chen, A. L. P. (2004). Hiding sensitive patterns in association rules mining. In COMPSAC'04.
  8. Moustakides, G. V. and Verykios, V. S. (2006). A max-min approach for hiding frequent itemsets. In ICDM'06.
  9. O'Leary, D. E. (1991). Knowledge discovery as a threat to database security. In Piatetsky-Shapiro, G. and Frawley, W. J., editors, Knowledge Discovery in Databases, pages 507-516. AAAI/MIT Press.
  10. Oliveira, S. R. M. and Zaïane, O. R. (2003). Protecting sensitive knowledge by data sanitization. In ICDM'03.
  11. Sun, X. and Yu, P. S. (2005). A border-based approach for hiding sensitive frequent itemsets. In ICDM'05.
  12. Verykios, V. S., Elmagarmid, A. K., Bertino, E., Saygin, Y., and Dasseni, E. (2004). Association rule hiding. IEEE TKDE, 16/4:434-447.
  13. Weng, C.-C., Chen, S.-T., and Chang, Y.-C. (2007). A novel algorithm for hiding sensitive frequent itemsets. In ISIS'07.
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Paper Citation


in Harvard Style

Gökçe H. and Abul O. (2010). A TRADEOFF BALANCING ALGORITHM FOR HIDING SENSITIVE FREQUENT ITEMSETS . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2010) ISBN 978-989-8425-28-7, pages 200-205. DOI: 10.5220/0003088302000205


in Bibtex Style

@conference{kdir10,
author={Harun Gökçe and Osman Abul},
title={A TRADEOFF BALANCING ALGORITHM FOR HIDING SENSITIVE FREQUENT ITEMSETS},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2010)},
year={2010},
pages={200-205},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003088302000205},
isbn={978-989-8425-28-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2010)
TI - A TRADEOFF BALANCING ALGORITHM FOR HIDING SENSITIVE FREQUENT ITEMSETS
SN - 978-989-8425-28-7
AU - Gökçe H.
AU - Abul O.
PY - 2010
SP - 200
EP - 205
DO - 10.5220/0003088302000205