Privacy preserving association rule mining

Y. Saygin, V. S. Verykios, A. K. Elmagarmid

Research output: Chapter in Book/Report/Conference proceedingConference contribution

105 Citations (Scopus)

Abstract

The current trend in the application space towards systems of loosely coupled and dynamically bound components that enables just-in-time integration jeopardizes the security of information that is shared between the broker, the requester, and the provider at runtime. In particular, new advances in data mining and knowledge discovery that allow for the extraction of hidden knowledge in an enormous amount of data, impose new threats on the seamless integration of information. We consider the problem of building privacy preserving algorithms for one category of data mining techniques, association rule mining. We introduce new metrics in order to demonstrate how security issues can be taken into consideration in the general framework of association rule mining, and we show that the complexity of the new heuristics is similar to that of the original algorithms.

Original languageEnglish
Title of host publicationProceedings - 12th International Workshop on Research Issues in Data Engineering
Subtitle of host publicationEngineering E-Commerce/E-Business Systems, RIDE-2EC 2002
EditorsEe-Peng Lim, Yanchun Zhang, Amjad Umar, Ming-Chien Shan
PublisherIEEE Computer Society
Pages151-158
Number of pages8
ISBN (Electronic)0769514804
DOIs
Publication statusPublished - 1 Jan 2002
Event12th International Workshop on Research Issues in Data Engineering: Engineering E-Commerce/E-Business Systems, RIDE-2EC 2002 - San Jose, United States
Duration: 24 Feb 200225 Feb 2002

Publication series

NameProceedings of the IEEE International Workshop on Research Issues in Data Engineering
Volume2002-January

Other

Other12th International Workshop on Research Issues in Data Engineering: Engineering E-Commerce/E-Business Systems, RIDE-2EC 2002
CountryUnited States
CitySan Jose
Period24/2/0225/2/02

Keywords

  • Association rules
  • Data engineering
  • Data mining
  • Data privacy
  • Data security
  • Educational institutions
  • Hardware
  • Information security
  • Internet
  • Space technology

ASJC Scopus subject areas

  • Software
  • Engineering (miscellaneous)
  • Hardware and Architecture

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  • Cite this

    Saygin, Y., Verykios, V. S., & Elmagarmid, A. K. (2002). Privacy preserving association rule mining. In E-P. Lim, Y. Zhang, A. Umar, & M-C. Shan (Eds.), Proceedings - 12th International Workshop on Research Issues in Data Engineering: Engineering E-Commerce/E-Business Systems, RIDE-2EC 2002 (pp. 151-158). [995109] (Proceedings of the IEEE International Workshop on Research Issues in Data Engineering; Vol. 2002-January). IEEE Computer Society. https://doi.org/10.1109/RIDE.2002.995109