DocumentCode :
188661
Title :
An Integer Linear Programming Scheme to Sanitize Sensitive Frequent Itemsets
Author :
Kagklis, Vasileios ; Verykios, Vassilios S. ; Tzimas, Giannis ; Tsakalidis, Athanasios K.
Author_Institution :
Comput. Eng. & Inf. Dept., Univ. of Patras, Patras, Greece
fYear :
2014
fDate :
10-12 Nov. 2014
Firstpage :
771
Lastpage :
775
Abstract :
In this paper, we propose a novel approach to address the frequent item set hiding problem, by formulating it as an integer linear program (ILP). The solution of the ILP points out the transactions that need to be sanitized in order to achieve the hiding of the sensitive frequent item sets, while the impact on other non-sensitive item sets is minimized. We present a novel heuristic approach to calculate the coefficients of the objective function of the ILP, while at the same time we minimize the side effects introduced by the hiding process. We also propose a sanitization algorithm that performs the hiding on the selected transactions. Finally, we evaluate the proposed method on real datasets and we compare the results of the newly proposed method with those of other state of the art approaches.
Keywords :
data mining; data privacy; integer programming; linear programming; set theory; ILP; frequent item set hiding problem; integer linear programming scheme; nonsensitive item sets; privacy preserving data mining; sanitization algorithm; sensitive frequent itemsets; Conferences; Data privacy; Itemsets; Linear programming; Silicon; Privacy preserving data mining; frequent sensitive itemset hiding; integer linear programming;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Tools with Artificial Intelligence (ICTAI), 2014 IEEE 26th International Conference on
Conference_Location :
Limassol
ISSN :
1082-3409
Type :
conf
DOI :
10.1109/ICTAI.2014.119
Filename :
6984555
Link To Document :
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