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Reseach Article

Knowledge Protection by Subjective Measure

by Cynthia Selvi P, Mohamed Shanavas A R
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 84 - Number 10
Year of Publication: 2013
Authors: Cynthia Selvi P, Mohamed Shanavas A R
10.5120/14613-2865

Cynthia Selvi P, Mohamed Shanavas A R . Knowledge Protection by Subjective Measure. International Journal of Computer Applications. 84, 10 ( December 2013), 23-26. DOI=10.5120/14613-2865

@article{ 10.5120/14613-2865,
author = { Cynthia Selvi P, Mohamed Shanavas A R },
title = { Knowledge Protection by Subjective Measure },
journal = { International Journal of Computer Applications },
issue_date = { December 2013 },
volume = { 84 },
number = { 10 },
month = { December },
year = { 2013 },
issn = { 0975-8887 },
pages = { 23-26 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume84/number10/14613-2865/ },
doi = { 10.5120/14613-2865 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:00:33.932267+05:30
%A Cynthia Selvi P
%A Mohamed Shanavas A R
%T Knowledge Protection by Subjective Measure
%J International Journal of Computer Applications
%@ 0975-8887
%V 84
%N 10
%P 23-26
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Basically a Data Mining system would generate thousands or even millions of patterns or rules. However all the generated patterns would not actually be interesting to any given user; In fact the interestingness of the patterns would be assessed only on the users' beliefs and expectations which is rather termed as subjective measure. When such interesting patterns are to be shared in a collaborative business environment, it would be more meaningful to restrict them based on the significance of individual items in the patterns to be protected. Hence, this work attempts to hide interesting patterns on the subjective measure and propose an algorithm which is tested for its effectiveness.

References
  1. Han J, and Kamber M, "Data Mining: Concepts and Techniques", Morgan Kaufmann Publishers – Reprint 2011.
  2. Atallah M, Bertino E, Elmagarmid A, Ibrahim M and Verykios V " Disclosure Limitation of Sensitive Rules", In Proc. of IEEE Knowledge and Data Engineering Workshop, pages 45–52, Chicago, Illinois, November 1999.
  3. Dasseni E, Verykios V. S, Elmagarmid A. K & Bertino E, "Hiding Association Rules by Using Confidence and Support", In Proc. of the 4th Information Hiding Workshop, pages 369– 383, Pittsburg, PA, April 2001.
  4. Saygin Y, Verykios V. S, and Clifton C, "Using Unknowns to Prevent Discovery of Association Rules", SIGMOD Record, 30(4):45–54, December 2001.
  5. Oliveira S. R. M, and Zaiane O. R, "Privacy preserving Frequent Itemset Mining", in the Proc. of the IEEE ICDM Workshop on Privacy, Security, and Data Mining, Pages 43-54, Maebashi City, Japan, December 2002.
  6. Oliveira S. R. M, and Zaiane O. R, "An Efficient One-Scan Sanitization for Improving the Balance between Privacy and Knowledge Discovery", Technical Report TR 03-15, June 2003.
  7. Yildz B, and Ergenc B, "Hiding Sensitive Predictive Frequent Itemsets", Proceedings of the International MultiConference of Engineers and Computer Scientists 2011, Vol-I.
  8. Cynthia Selvi P, Mohamed Shanavas A. R, "An Improved Item-based Maxcover Algorithm to Protect Sensitive Patterns in Large Databases", IOSR-Journal on Computer Engineering, Volume 14, Issue 4 (Sep-Oct, 2013), PP 01-05, DOI. 10. 9790/0661-1440105.
  9. The Dataset used in this work for experimental analysis was generated using the generator from IBM Almaden Quest research group and is publicly available from http://fimi. ua. ac. be/data/.
  10. Pavon J, Viana S, Gomez S, "Matrix Apriori: speeding up the search for frequent patterns," Proc. 24th IASTED International Conference on Databases and Applications, 2006, pp. 75-82.
Index Terms

Computer Science
Information Sciences

Keywords

Subjective measure Restrictive patterns Sensitive transactions Maxcover Sanitization.