Title :
A Survey on Privacy Preserving Data Mining
Author :
Wang, Jian ; Luo, Yongcheng ; Zhao, Yan ; Le, JiaJin
Author_Institution :
Coll. of Inf. Sci. & Technol., Donghua Univ., Shanghai, China
Abstract :
Privacy preserving becomes an important issue in the development progress of data mining techniques. Privacy preserving data mining has become increasingly popular because it allows sharing of privacy-sensitive data for analysis purposes. So people have become increasingly unwilling to share their data, frequently resulting in individuals either refusing to share their data or providing incorrect data. In turn, such problems in data collection can affect the success of data mining, which relies on sufficient amounts of accurate data in order to produce meaningful results. In recent years, the wide availability of personal data has made the problem of privacy preserving data mining an important one. A number of methods have recently been proposed for privacy preserving data mining of multidimensional data records. This paper intends to reiterate several privacy preserving data mining technologies clearly and then proceeds to analyze the merits and shortcomings of these technologies.
Keywords :
data analysis; data mining; data privacy; data collection; data mining; data privacy preserving; multidimensional data record; privacy-sensitive data; Data analysis; Data mining; Data privacy; Databases; Diseases; Educational institutions; Hospitals; Information science; Multidimensional systems; Protection; data mining; privacy preserving;
Conference_Titel :
Database Technology and Applications, 2009 First International Workshop on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3604-0
DOI :
10.1109/DBTA.2009.147