Hiding sensitive itemsets by inserting dummy transactions
Tzung‐Pei Hong, Jerry Chun‐Wei Lin, Chia-Ching Chang, Shyue-Liang Wang · 2011
The privacy-preserving data mining (PPDM) has become an important issue in recent years. In this paper, a greedy-based approach for hiding sensitive itemsets by inserting dummy transactions is proposed. It computes the maximal number of transactions to be inserted into the original database for totally hiding sensitive itemsets. Experimental results are also performed to evaluate the performance of the proposed approach.