Hiding Sensitive Predictive Frequent Itemsets

In this work, we propose an itemset hiding algorithm with four versions that use different heuristics in selecting the item in itemset and the transaction for distortion. The main strengths of itemset hiding algorithm can be stated as i) it works without pre-mining so privacy breech caused by reveal...

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Bibliographic Details
Published inWorld Congress on Engineering 2012. July 4-6, 2012. London, UK Vol. 2188; pp. 339 - 345
Main Authors Yildiz, Bans, Ergenc, Belgin
Format Journal Article
LanguageEnglish
Published 01.03.2010
Subjects
Algorithms
Distortion
Heuristic
Run time (computers)
Scientists
Side effects
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Summary:In this work, we propose an itemset hiding algorithm with four versions that use different heuristics in selecting the item in itemset and the transaction for distortion. The main strengths of itemset hiding algorithm can be stated as i) it works without pre-mining so privacy breech caused by revealing frequent itemsets in advance is prevented and efficiency is increased, ii) base algorithm (Matrix-Apriori) works without candidate generation so efficiency is increased, iii) sanitized database and frequent itemsets of this database are given as outputs so no post-mining is required and iv) simple heuristics like the length of the pattern and the frequency of the item in the pattern are used for selecting the item for distortion. We compare versions of our itemset hiding algorithm by their side effects, runtimes and distortion on original database.
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ISSN:2078-0958