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