@inproceedings{10cf297165d649d6857c749f87dbe428,
title = "Privacy preserving association rule mining",
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.",
keywords = "Association rules, Data engineering, Data mining, Data privacy, Data security, Educational institutions, Hardware, Information security, Internet, Space technology",
author = "Y. Saygin and Verykios, {V. S.} and Elmagarmid, {A. K.}",
note = "Publisher Copyright: {\textcopyright} 2002 IEEE.; 12th International Workshop on Research Issues in Data Engineering: Engineering E-Commerce/E-Business Systems, RIDE-2EC 2002 ; Conference date: 24-02-2002 Through 25-02-2002",
year = "2002",
doi = "10.1109/RIDE.2002.995109",
language = "English",
series = "Proceedings of the IEEE International Workshop on Research Issues in Data Engineering",
publisher = "IEEE Computer Society",
pages = "151--158",
editor = "Ee-Peng Lim and Yanchun Zhang and Amjad Umar and Ming-Chien Shan",
booktitle = "Proceedings - 12th International Workshop on Research Issues in Data Engineering",
address = "United States",
}