Hiding Sensitive Association Rules on Stars
Shyue-Liang Wang, Tzung‐Pei Hong, Yu‐Chuan Tsai, Hung‐Yu Kao · 2010
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.