CSE 634Data Mining Techniques

Association Rules Hiding (Not Mining)

Prateek Duble

(105301354)

Course Instructor: Prof. Anita Wasilewska

State University of New York, Stony Brook

State University of New York, Stony Brook 2

Association Rule Hiding

New & Data Privacy related Concept Large repositories of data contain sensitive information that must be

protected against unauthorized access. The protection of the confidentiality of this information has been a long-

term goal for the database security research community and for the government statistical agencies.

User

Changed Database

Data Mining

Association Rules

Hide Sensitive Rules

State University of New York, Stony Brook 3

Association Rule Hiding

There are various algorithms for hiding a group of association rules, which is characterized as sensitive.

One rule is characterized as sensitive if its disclosure risk is above a certain privacy threshold.

Sometimes, sensitive rules should not be disclosed to the public since, among other things, they may be used for inferring sensitive data, or they may provide business competitors with an advantage.

Association Rule Hiding Techniques Blocking-based Technique (Saygin, Verykios, Clifton) Distortion-based (Sanitization) Technique – (Oliveira,

Zaiane, Verykios, Dasseni)

State University of New York, Stony Brook 4

More Association Rule Hiding (Papers)

[Alexandre Evfimievski, Ramakrishnan Srikant, Rakesh Agrawal, Johannes Gehrke. Privacy Preserving Mining of Association Rules.Privacy Preserving Mining of Association Rules. SIGKDD 2002, Edmonton, Alberta Canada.

Murat Kantarcioglou and Chris Clifton, Privacy Preserving Distributed Privacy Preserving Distributed Mining of Association Rules on Horizontally Partitioned DataMining of Association Rules on Horizontally Partitioned Data, In Proceedings of the ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery (2002).

Jaideep Vaidya and Chris Clifton, Privacy Preserving Association Rule Privacy Preserving Association Rule Mining in Vertically Partitioned DataMining in Vertically Partitioned Data, In the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2002)

Stanley R. M. Oliveira and Osmar R. Zaïane. Algorithms for Balacing Algorithms for Balacing Privacy and Knowledge Discovery in Association Rule MiningPrivacy and Knowledge Discovery in Association Rule Mining.  In Proc. of the Seventh International Database Engineering & Applications Symposium (IDEAS'03), pp. 54-63, Hong Kong, July 16-18, 2003.

Yucel Saygin, Vassilios Verykios, and Chris Clifton, Using Unknowns to Using Unknowns to Prevent Discovery of Association RulesPrevent Discovery of Association Rules, SIGMOD Record 30 (2001), no. 4, 45–54.

S. Verykios, Ahmed K. Elmagarmid, Bertino Elisa, Yucel Saygin, and Dasseni Elena, Association Rule HidingAssociation Rule Hiding, IEEE Transactions on Knowledge and Data Engineering (2003).

State University of New York, Stony Brook 5

Thanks for Your Patience