CSE 634 Data Mining Techniques - PowerPoint PPT Presentation

About This Presentation
Title:

CSE 634 Data Mining Techniques

Description:

CSE 634 Data Mining Techniques Association Rules Hiding (Not Mining) Prateek Duble (105301354) Course Instructor: Prof. Anita Wasilewska State University of New York ... – PowerPoint PPT presentation

Number of Views:168
Avg rating:3.0/5.0
Slides: 6
Provided by: csSunysb
Category:

less

Transcript and Presenter's Notes

Title: CSE 634 Data Mining Techniques


1
CSE 634Data Mining Techniques
  • Association Rules Hiding (Not Mining)
  • Prateek Duble
  • (105301354)
  • Course Instructor Prof. Anita Wasilewska
  • State University of New York, Stony Brook

2
Association Rule Hiding
  • Changed
  • Database
  • 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.

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)

4
More Association Rule Hiding (Papers)
  • Alexandre Evfimievski, Ramakrishnan Srikant,
    Rakesh Agrawal, Johannes Gehrke. Privacy
    Preserving Mining of Association Rules. SIGKDD
    2002, Edmonton, Alberta Canada.
  • Murat Kantarcioglou and Chris Clifton, Privacy
    Preserving Distributed Mining 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 Mining 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 Privacy 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 Prevent Discovery of
    Association Rules, SIGMOD Record 30 (2001), no.
    4, 4554.
  • S. Verykios, Ahmed K. Elmagarmid, Bertino Elisa,
    Yucel Saygin, and Dasseni Elena, Association Rule
    Hiding, IEEE Transactions on Knowledge and Data
    Engineering (2003).

5
Thanks for Your Patience
Write a Comment
User Comments (0)
About PowerShow.com