Hiding sequences

Proceedings - International Conference on Data Engineering

Volumn , Issue , 2007, Pages 146-156

  Abul, Osman ^a   Atzori, Maurizio ^a   Bonchi, Francesco ^a   Giannotti, Fosca ^a  

^a ISTI CNR   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

ASSOCIATIVE PROCESSING; CHLORINE COMPOUNDS; DATABASE SYSTEMS; NUCLEAR PROPULSION; TECHNOLOGY;

ASSOCIATION RULES; BASIC BUILDING BLOCKS; DATA ENGINEERING; DATABASE SECURITY; EXPERIMENTAL EVALUATIONS; FREQUENT ITEMSETS MINING; INTERNATIONAL CONFERENCES; NP-HARDNESS; PROBLEM STATEMENTS; REAL-WORLD DATA; RELEVANT PATTERNS; SANITIZATION ALGORITHM;

KNOWLEDGE BASED SYSTEMS;

EID: 48349102436     PISSN: 10844627     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDEW.2007.4400985     Document Type: Conference Paper

References (28)

1. D. Agrawal and C. C. Aggarwal. On the design and quantification of privacy preserving data mining algorithms. In Proceedings of the 20th ACM PODS, pages 247 255, 2001.
2. R. Agrawal and R. Srikant. Mining sequential patterns. In Eleventh ICDE'95, pages 3-14, Taipei, Taiwan, 1995.
3. R. Agrawal and R. Srikant. Privacy-preserving data mining. In Proceedings of the 2000 ACM SIGMOD. pagos 430 450, 2000.
4. M.Atallah, E. Bertino. A. Elmagarmid, M. Ibrahim, and V. S. Verykios. Disclosure limitation of sensitive rules. In Proceedings of the 1999 IEEE KDEX. pages 45-52, 1999.
5. M. Atzori, F. Bonchi, F. Giannotti, and D. Pedreschi. Anonymity preserving pattern discovery. VLDB Journal., Accepted for publication 2006.
6. M. Atzori, F. Bonchi, F. Giannotti, and D. Pedreschi. Blocking anonymity threats raised by frequent itemset mining. In Proceedings of the Fifth IEEE ICDM, pages 501 504, 2005.
7. H. Cao, N. Mumoulis, and D. W. Cheung. Mining frequent, spatio-temporal sequential patterns. In Proceedings of the 5th ICDM (2005), 27-30 November 2005, Houston, Texas. USA.
8. C. Clifton and D. Marks. Security and privacy implications of data mining. In Proceedings of the 1996 ACM SIGMOD, pages 15 19, Feb. 1996.
9. E. Dasseni, V. S. Verykios, A. K. Elinagarmid, and E. Bertino. Hiding association rules by using confidence and support. In Proceedings of the 4th International Workshop on Information Hiding, pages 360 383, 2001.
10. W. Du and Z. Zhan. Using randomized response techniques for privacy-preserving data mining. In Proceedings of the Ninth ACM KDD, pages 505-510, 2003.
11. A. Evfimicvski, R. Srikant, R. Agrawal, and J. Gehrke. Privacy preserving mining of association rules. In Proceedings of the Eighth ACM KDD, pages 343 364, 2002.
12. E. Frentzos, K. Gratsins. N. Pelekis, and Y. Theodoridis. Nearest neighbor search on moving object trajectories. In SSTD'05, 2005.
13. A. Friedman, A. Schuster, and R. Wolff, k-anonymous decision tree induction. In Proc. of PKDD '06, pages 151 162, Berlin, Germany, 2006. Springer-Verlag.
14. M. R. Garcy and D. S. Johnson. Computers and Intraettibility: A Guide, to the Theory of NP-Completeness. W. H. Freeman & Co., New York, NY, USA, 1070.
15. F. Giannotti, A. Mazzoni, S. Puntoni, and C. Ronso. Synthetic generation of cellular network positioning data. In 13th ACM International Symposium on Advances in Geografic Information Systems (ACMGIS'05). Bremen, Germany, 2005.
16. M. Kantarcioglu, J. Jin, and C. Clifton. When do data mining results violate privacy? In Proceedings of the Tenth ACMKDD, pages 599 604. 2004.
17. G. Lee, C.-Y. Chang, and A. L. P. Chen. Hiding sensitive patterns in association rules mining. In 28th Annual International Computer Software and Applications Conference (COMPSAC 2004), pages 424 429, 2004.
18. N. Manioulis, H. Cao, G. Kollios. M. Hadjieleftheriou, Y. Tao, and D. W. Cheung. Mining, indexing, and querying historical spatioteniporal data. In Proceedings of the Tenth ACM KDD.
19. S. Menon, S. Sarkar, and S. Mukherjee. Maximizing accuracy of shared databases when concealing sensitive patterns. Information Systems Research. 16(3):256 270. 2005.
20. D. E. O'Leary. Knowledge discovery as a threat to database security. In G. Piatetsky-Shapiro and W. J. Frawley, editors, Knowledge Discovery in Databases, pages 507 516. AAAI/MIT Press, 1991.
21. S. R. M. Oliveira and O. R. Zaïane. Protecting sensitive knowledge by data sanitization. In Proceedings of the Third IEEE ICDM, pages 211 218, 2003.
22. E. D. Pontikakis, A. A. Tsitsonis, and V. S. Verykios. An experimental study of distortion-based techniques for association rule hiding. In Proceedings of the 18th Conference on Database Security (DBSEC 2004), pages 325 339, 2004.
23. S. Rizvi and J. R. Haritsa. Maintaining data privacy in association rule mining. In Proceedings of the 28th VLDB, 2002.
24. Y. Saygin, V. S. Verykios, and C. Clifton. Using unknowns to prevent discovery of association rules. ACM SIGMOD Record, 30(4):45 54, 2001.
25. Y. Saygin, V. S. Verykios, and A. K. Elmagannid. Privacy preserving association rule mining. In Proceedings of the 2002 International Workshop on Rescarch Issues in Data Engineering: Engineering E-Commerce/E-Business Systems (RIDE 2002), 2002.
26. X. Sun and P. S. Yu. A border-based approach for hiding sensitive frequent itemsets. In Proceedings of the Fifth IEEE ICDM, pages 426 433, 2005.
27. V. S. Verykios, E. Bertino, I. N. Fovino, L. P. Provenza, Y. Saygin, and Y. Theodoridis. State-of-the-art in privacy preserving data mining. ACM SIGMOD Record, 33(1):50 57, 2004.
28. V. S. Verykios, A. K. Emagarmid, E. Bertino, Y. Saygin, and E. Dasseni. Association rule hiding. IEEE Transactions on Knowledge and Data Engineering, 16(4) :434 447, 2004.