Title :
Hiding Sensitive Association Rules on Stars
Author :
Wang, Shyue-Liang ; Hong, Tzung-Pei ; Tsai, Yu-Chuan ; Kao, Hung-Yu
Author_Institution :
Dept. of Inf. Manage., Eng. Nat. Univ. of Kaohsiung, Kaohsiung, Taiwan
Abstract :
Current technology for association rules hiding mostly applies to data stored in a single transaction table. This work presents a novel algorithm for hiding sensitive association rules in data warehouses. A data warehouse is typically made up of multiple dimension tables and a fact table as in a star schema. Based on the strategies of reducing the confidence of sensitive association rule and without constructing the whole joined table, the proposed algorithm can effectively hide multi-relational association rules. Examples and analyses are given to demonstrate the efficacy of the approach.
Keywords :
data encapsulation; data mining; data warehouses; data warehouses; fact table; multi-relational association rules; multiple dimension tables; sensitive association rules hiding; single transaction table; star schema; Algorithm design and analysis; Association rules; Data privacy; Data warehouses; Itemsets; Association rule; Data mining; Hiding; Multi-relational; Privacy preserving;
Conference_Titel :
Granular Computing (GrC), 2010 IEEE International Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
978-1-4244-7964-1
DOI :
10.1109/GrC.2010.123