Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6968
Title: Knowledge hiding from tree and graph databases
Authors: Abul, Osman
Gökçe, Harun
Keywords: Data publication
Data mining
Sensitive knowledge hiding
Tree hiding
Graph hiding
Issue Date: 2012
Publisher: Elsevier Science Bv
Abstract: Sensitive knowledge hiding is the problem of removing sensitive knowledge from databases before publishing. The problem is extensively studied in the context of relational databases to hide frequent itemsets and association rules. Recently, sequential pattern hiding from sequential (both sequence and spatio-temporal) databases has been investigated [1]. With the ever increasing versatile application demands, new forms of knowledge and databases should be addressed as well. In this work, we address the knowledge hiding problem in the context of tree and graph databases. For these databases efficient frequent pattern mining algorithms have already been developed in the literature. Since, some of the discovered patterns may be attributed as sensitive, we develop appropriate sanitization techniques to protect the privacy of the sensitive patterns. (C) 2011 Elsevier B.V. All rights reserved.
URI: https://doi.org/10.1016/j.datak.2011.10.002
https://hdl.handle.net/20.500.11851/6968
ISSN: 0169-023X
1872-6933
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Show full item record

CORE Recommender

SCOPUSTM   
Citations

6
checked on Sep 23, 2022

WEB OF SCIENCETM
Citations

6
checked on Sep 24, 2022

Page view(s)

36
checked on Dec 26, 2022

Google ScholarTM

Check

Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.