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A Conceptual Framework for Hiding Sensitive Association Rules

Published on July 2016 by Geeta S. Navale, Suresh N. Mali
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International Conference on Internet of Things, Next Generation Networks and Cloud Computing
Foundation of Computer Science USA
ICINC2016 - Number 1
July 2016
Authors: Geeta S. Navale, Suresh N. Mali
6c553f7f-d6b2-41ff-a56f-aa874e998a77

Geeta S. Navale, Suresh N. Mali . A Conceptual Framework for Hiding Sensitive Association Rules. International Conference on Internet of Things, Next Generation Networks and Cloud Computing. ICINC2016, 1 (July 2016), 18-21.

@article{
author = { Geeta S. Navale, Suresh N. Mali },
title = { A Conceptual Framework for Hiding Sensitive Association Rules },
journal = { International Conference on Internet of Things, Next Generation Networks and Cloud Computing },
issue_date = { July 2016 },
volume = { ICINC2016 },
number = { 1 },
month = { July },
year = { 2016 },
issn = 0975-8887,
pages = { 18-21 },
numpages = 4,
url = { /proceedings/icinc2016/number1/25524-4767/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Internet of Things, Next Generation Networks and Cloud Computing
%A Geeta S. Navale
%A Suresh N. Mali
%T A Conceptual Framework for Hiding Sensitive Association Rules
%J International Conference on Internet of Things, Next Generation Networks and Cloud Computing
%@ 0975-8887
%V ICINC2016
%N 1
%P 18-21
%D 2016
%I International Journal of Computer Applications
Abstract

Data mining process is used to extract knowledge from the database. Large numbers of data mining tools are available to get the useful information. These tools can be utilized to break the privacy and security of useful sensitive information present in the database. This sensitive information may be personal information, patterns, facts etc. This sensitive information if mined will result in loss of business logics of database owners. Hence there is a need to hide sensitive knowledge. The hiding process must ensure that the knowledgeshould be mined without disclosing sensitive association rules to the users with minimum impact on nonsensitive association rules. Also, intentional as well as unintentional attackers who are trying to retrieve sensitive association rules should not be successful once they are hidden. In this paper, the authorspropose a methodology to hide sensitive association rules.

References
  1. Agrawal, R. , Imielinski, T. , Swami, "A. : Mining Association Rules between Sets of Items in Large Databases," ACM SIGMOD International Conference on Management of Data (SIGMOD'93), Washington D. C. , USA , pp. 207–216, May 1993
  2. Geng L. , Hamilton, H. J. , "Interestingness Measures For Data Mining:A Survey," ACM Comput. Surv. (CSUR) 38(3), 9, 2006.
  3. McGarry, K, "A survey of Interestingness Measures for Knowledge Discovery," Knowl. Eng. Rev. 20(1), pp. 39–61, 2005.
  4. G. Dong and J. Li, "Interestingness of Discovered Association Rules in terms of Neighbourhood-Based Unexpectedness," Second Paci?c-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'98), pp. 72-86, 1998.
  5. Lallich, S. , Teytaud, O. , Prudhomme, E. , "Association Rule Interestingness: Measure and Statistical Validation," Qual. Measur. Data Min. 43, pp. 251–276, 2006.
  6. A. A. Freitas, "On Rule Interestingness Measures," Elsevier, Knowledge-Based Systems 12, pp. 309–315,1999.
  7. Dasseni E, Verykios VS, Elmagarmid AK, Bertino E. , "Hiding Association Rules by Using Confidence and Support," In: Proceedings of the 4th International Workshop on Information Hiding, pp. 369–383, 2001.
  8. Verykios VS, Pontikakis ED, Theodoridis Y, Chang L. , "Efficient Algorithms for Distortion and Blocking Techniques in Association Rule Hiding," Distributed Parallel Databases, pp. 22:85–104, 2007.
  9. Wu Y-H, Chiang C-M, Chen ALP. , "Hiding Sensitive Association Rules with Limited Side Effects," IEEE Trans Knowledge Data Eng, pp. 19:29–42, 2007.
  10. Gkoulalas-Divanis A, Verykios VS. , "Hiding Sensitive Knowledge Without Side Effects," Knowledge Inf Syst, pp. 20:263–299, 2009.
  11. Gkoulalas-Divanis A, Verykios VS. , "Exact Knowledge Hiding Through Database Extension," IEEE Trans Knowledge Data Eng, pp. 21:699–713, 2009.
Index Terms

Computer Science
Information Sciences

Keywords

Privacy Preserving Data Mining Association Rules Hiding Knowledge Hiding