Privacy Preserving In Data Mining: A Survey - Rani, Smita; Saxena, Akash (International Journal of Computer Sciences and Engineering, 2025)
Todays scenario conversion of data from the databases or data warehouse to avail the users is one of the challenging tasks in data mining. There is high risk of data loss and these losses of data sometimes create high risk for users for their sensitive data; because large amount of data gets publish on daily basis. Data mining comes now a day has lots of necessary techniques for privacy preserving. In the past decennary the evolution of various data mining techniques, privacy preservation in data mining becomes an important issues. Basically privacy preservation of data mining provides the facility of sharing of critical data for analysis purposes. The problem of privacy preserving data mining becomes very crucial due to the possibility of occurrence of personal data. Essential parameter used for preserving the privacy of data mining is efficiency, time, cost, accuracy. To achieve the high privacy user have to compromise accuracy, time and cost. This survey paper mainly discussed the introduction of Data Mining, some of the proposed algorithm for privacy preserving in data mining and framework of privacy preservation. Several privacy preservation techniques in data mining based upon different parameters to measure Information Loss Rate (ILR) and Privacy Ratio (PR) are also discussed in this paper.