privacy-preserving data mining

Privacy-preserving data mining involves analyzing data to find useful patterns or insights while protecting individuals’ personal information. It uses techniques to ensure sensitive details remain confidential, such as anonymizing data or applying methods that prevent the identification of individuals. This way, organizations can gain valuable knowledge from large datasets—like trends or behaviors—without compromising privacy. The goal is to balance data utility with privacy safeguards, enabling insights that benefit both organizations and individuals, especially in sensitive areas like healthcare, finance, or social data.