GA-based Approach for Hiding Sensitive Itemsets by Transaction Insertion

Data mining technology is used to derive useful knowledge from large databases to aid corporate decision-making. The process of data collection and dissemination may, however, cause privacy concerns. Thus, privacy-preserving data mining (PPDM) has become an important issue. In this paper, an evolutionary privacy -preserving data mining method is proposed for finding appropriate itemsets within inserted transactions while hiding sensitive itemsets. An experiment is conducted to evaluate the performance of the proposed approach.