Hiding Frequent Patterns in the Updated Database

Abstract

Sensitive frequent pattern hiding is an important issue in privacy preserving data mining. In this era of information explosion and rapid development of the Internet, the data stored in the database is usually continuously updated. Existing frequent pattern hiding algorithms gradually become inadequate because those algorithms are originally designed for static database and thus they cannot handle incremental datasets effectively and efficiently. In order to solve this problem, we propose an incremental mechanism and design a data structure in this paper to hide sensitive frequent patterns in the incremental environment. In this mechanism, the transaction data and sensitive patterns are stored in two types of trees. The proposed algorithm can efficiently find related transactions by links between these two types of trees. Experiment results show that the proposed method can efficiently hide sensitive frequent patterns in the incremental environment.