Privacy Preserving Data Mining and its Applications: A Survey of Recent Developments

Numerous services, including those in the fields of health care, finance, cyber security, business, and transportation, have benefited from Data Mining. However, a lot of the data may contain sensitive personal information, which presents privacy risks. A lot of privacy preservation methods have been introduced in recent times. These include clustering, k-anonymity, classification, association rule,
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-diverse, distributed privacy preservation and so on. This research study focuses on the recent developments done in this field and presents a brief outline of the considered research works.