Analysis of Privacy Preserving Approaches in High Utility Pattern Mining

With the significant increase of information sharing in various areas, it has been an important issue to prevent personal information from being disclosed to abnormal users. Pattern mining is one of data mining technique for extracting interesting pattern information from massive databases. Therefore, sensitive patterns belonging to personal information can be disclosed to abnormal users through pattern mining methods. A sanitization approach that modifies a given database is one of the most common approach for achieving privacy preserving. In this paper, we introduce and analyze various methods for achieving privacy preserving in high utility pattern mining based on sanitization approaches.