Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6174
Title: A Tradeoff Balancing Algorithm For Hiding Sensitive Frequent Itemsets
Authors: Gökçe, Harun
Abul, Osman
Keywords: Data mining
Frequent itemset mining
Privacy
Sensitive knowledge hiding
Issue Date: 2010
Publisher: Scitepress
Source: International Conference on Knowledge Discovery and Information Retrieval (KDIR 2010) -- OCT 25-28, 2010 -- Valencia, SPAIN
Abstract: Sensitive frequent itemset hiding problem is typically solved by applying a sanitization process which transforms the source database into a release version. The main challenge in the process is to preserve the database utility while ensuring no sensitive knowledge is disclosed, directly or indirectly. Several algorithmic solutions based on different approaches are proposed to solve the problem. We observe that the available algorithms are like seesaws as far as both effectiveness and efficiency performances are considered. However, most practical domains demand for solutions with satisfactory effectiveness/efficiency performances, i.e., solutions balancing the tradeoff between the two. Motivated from this observation, in this paper, we present yet a simple and practical frequent itemset hiding algorithm targeting the balanced solutions. Experimental evaluation, on two datasets, shows that the algorithm indeed achieves a good balance between the two performance criteria.
URI: https://hdl.handle.net/20.500.11851/6174
ISBN: 978-989-8425-28-7
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

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