An efficient sanitization algorithm for balancing information privacy and knowledge discovery in association patterns mining

Data and Knowledge Engineering

Volumn 65, Issue 3, 2008, Pages 463-484

  Wang, En Tzu ^a   Lee, Guanling ^b  

^a NATIONAL TSING HUA UNIVERSITY   (Taiwan)

^b NATIONAL DONG HWA UNIVERSITY   (Taiwan)

Author keywords

Data mining; Frequent pattern; Probability policy; Sanitization process; Sensitive pattern

Indexed keywords

ALGORITHMS; COMPUTATIONAL COMPLEXITY; DATA PRIVACY; DATABASE SYSTEMS; INFORMATION RETRIEVAL; PROBLEM SOLVING;

FREQUENT PATTERN; INFORMATION DISCOVERY; PROBABILITY POLICY; SANITIZATION ALGORITHMS; SENSITIVE PATTERN;

DATA MINING;

EID: 43049091932     PISSN: 0169023X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.datak.2007.12.005     Document Type: Article

References (24)

1. M. Atallah, E. Bertino, A. Elmagarmid, M. Ibrahim, V. Verykios, Disclosure limitation of sensitive rules, in: Proceedings of the IEEE Knowledge and Data Engineering Exchange Workshop (KDEX'99), Chicago, Illinois, 1999, pp. 45-52.
2. Atzori M., Bonchi F., Giannotti F., and Pedreschi D. k-Anonymous patterns. Proceedings of the 9th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD2005). Lecture Notes in Computer Science vol. 3721 (2005), Springer, Porto, Portugal 10-21
3. M. Atzori, F. Bonchi, F. Giannotti, D. Pedreschi, Blocking anonymity threats raised by frequent itemset mining, in: Proceedings of the Fifth IEEE International Conference on Data Mining (ICDM'05), Texas, USA, 2005, pp. 561-564.
4. R. Agrawal, R. Srikant, Fast algorithms for mining association rules in large databases, in: Proceedings of the 20th International Conference on Very Large Databases (VLDB'94), Santiago, Chile, 1994, pp. 487-499.
5. R. Agrawal, R. Srikant, Privacy preserving data mining, in: Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD'00), Dallas, Texas, 2000, pp. 439-450.
6. A. Evfimievski, J. Gehrke, R. Srikant, Limiting privacy breached in privacy preserving data mining, in: Proceedings of the Twenty-second ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems (PODS'03), San Diego, California, 2003, pp. 211-222.
7. A. Evfimievski, R. Srikant, R. Agrawal, J. Gehrke, Privacy preserving mining of association rules, in: Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery in Databases and Data Mining (KDD'02), Alberta, Canada, 2002, pp. 217-228.
8. Kantarcioglu M., and Clifton C. Privacy-preserving distributed mining of association rules on horizontally partitioned data. IEEE Transactions on Knowledge and Data Engineering 16 9 (2004) 1026-1037
9. G. Lee, C.Y. Chang, A.L.P Chen, Hiding sensitive patterns in association rules mining, in: Proceedings of the 28th IEEE Annual International Computer Software and Applications Conference (COMPSAC'04), Hong Kong, China, 2004, pp. 424-429.
10. Lindell Y., and Pinkas B. Privacy preserving data mining. Journal of Cryptology 15 3 (2002) 177-206
11. G.V. Moustakides, V.S. Verykios, A max-min approach for hiding frequent itemsets, in: Proceedings of the IEEE ICDM Workshop on Privacy Aspects of Data Mining (PADM2006), Hong Kong, China, 2006, pp. 502-506.
12. S.R.M. Oliveira, O.R. Zai{dotless}̈ane, Privacy preserving frequent itemset mining, in: Proceedings of the IEEE ICDM Workshop on Privacy, Security, and Data Mining, Maebashi City, Japan, 2002, pp. 43-54.
13. S.R.M. Oliveira, O.R. Zai{dotless}̈ane, Algorithms for balancing privacy and knowledge discovery in association rule mining, in: Proceedings of the 7th IEEE International Database Engineering and Applications Symposium (IDEAS2003), Hong Kong, China, 2003, pp. 54-65.
14. S.R.M. Oliveira, O.R. Zai{dotless}̈ane, Protecting sensitive knowledge by data sanitization, in: Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM'03), Melbourne, Florida, USA, 2003, pp. 613-616.
15. S.R.M. Oliveira, O.R. Zai{dotless}̈ane, Y. Saygin, Secure association rule sharing, advances in knowledge discovery and data mining, in: Proceedings of the 8th Pacific-Asia Conference (PAKDD2004), Sydney, Australia, 2004, pp. 74-85.
16. Oliveira S.R.M., and Zai{dotless}̈ane O.R. A unified framework for protecting sensitive association rules in business collaboration. International Journal of Business Intelligence and Data Mining l 3 (2006) 247-287
17. Pinks B. Cryptographic techniques for privacy-preserving data mining. ACM SIGKDD Explorations Newsletter 4 2 (2002) 12-19
18. S.J. Rizvi, J.R. Haritsa, Maintaining data privacy in association rule mining, in: Proceedings of the 28th International Conference on Very Large Data Bases (VLDB'02), Hong Kong, China, 2002, pp. 682-693.
19. X. Sun, P.S. Yu, A border-based approach for hiding sensitive frequent itemsets, in: Proceedings of the Fifth IEEE International Conference on Data Mining (ICDM'05), Texas, USA, 2005, pp. 426-433.
20. J. Vaidya, C.W. Clifton, Privacy preserving association rule mining in vertically partitioned data, in: Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'02), Edmonton, Canada, 2002, pp. 639-644.
21. Verykios V.S., Elmagarmid A.K., Bertino E., Saygin Y., and Dasseni E. Association rule hiding. IEEE Transactions on Knowledge and Data Engineering 16 4 (2004) 434-447
22. E.T. Wang, G. Lee, Y.T. Lin, A novel method for protecting sensitive knowledge in association rules mining, in: Proceedings of the 29th IEEE Annual International Computer Software and Applications Conference (COMPSAC'05), Edinburgh, Scotland, 2005, pp. 511-516.
23. Z. Wang, W. Wang, B. Shi, S.H. Boey, Preserving private knowledge in frequent pattern mining, in: Proceedings of the Sixth IEEE International Conference on Data Mining Workshops (ICDMW'06), Hong Kong, China, 2006, pp. 530-534.
24. Z. Wang, W. Wang, B. Shi, Blocking inference channels in frequent pattern sharing, in: Proceedings of the 23rd International Conference on Data Engineering (ICDE'07), Istanbul, Turkey, 2007, pp. 1425-1429.