A Review on Privacy Preserving Data Mining Techniques and Applications

In the realm of data mining, techniques such as clustering, association rule mining, and classification serve as powerful tools to unveil concealed insights within datasets. However, the proliferation of sensitive personal information in data sources has sparked heightened privacy concerns. In response, a myriad of privacy-protection solutions have emerged. This paper aims to scrutinize the latest advancements in data mining privacy protection and furnish a comprehensive review of anonymization approaches. By delving into the intricacies of safeguarding personal data, the study contributes to the ongoing discourse on data privacy and security in the era of big data. It navigates the delicate balance between the promises of data mining and the imperative to shield personal information.