Title :
Multi-table association rules hiding
Author :
Wang, Shyue-Liang ; Hong, Tzung-Pei ; Tsai, Yu-Chuan ; Kao, Hung-Yu
Author_Institution :
Dept. of Inf. Manage., Nat. Univ. of Kaohsiung, Kaohsiung, Taiwan
fDate :
Nov. 29 2010-Dec. 1 2010
Abstract :
Many approaches for preserving association rule privacy, such as association rule mining outsourcing, association rule hiding, and anonymity, have been proposed. In particular, association rule hiding on single transaction table has been well studied. However, hiding multi-relational association rule in data warehouses is not yet investigated. This work presents a novel algorithm to hide predictive association rules on multiple tables. Given a target predictive item, a technique is proposed to hide multi-relational association rules containing the target item without joining the multiple tables. Examples and analyses are given to demonstrate the efficiency of the approach.
Keywords :
data encapsulation; data mining; data privacy; data warehouses; multitable association rules hiding; privacy; single transaction table; association rule; data mining; hiding; multi-relational; privacy preserving;
Conference_Titel :
Intelligent Systems Design and Applications (ISDA), 2010 10th International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4244-8134-7
DOI :
10.1109/ISDA.2010.5687088