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Privacy Preserving Data Mining: How Far Can We Go?

Privacy Preserving Data Mining: How Far Can We Go?
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Author(s): Aris Gkoulalas-Divanis (Vanderbilt University, USA) and Vassilios S. Verykios (University of Thessaly, Greece)
Copyright: 2010
Pages: 17
Source title: Data Mining in Public and Private Sectors: Organizational and Government Applications
Source Author(s)/Editor(s): Antti Syvajarvi (University of Lapland, Finland) and Jari Stenvall (Tampere University, Finland)
DOI: 10.4018/978-1-60566-906-9.ch007

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Abstract

Since its inception in 2000, privacy preserving data mining has gained increasing popularity in the data mining research community. This line of research can be primarily attributed to the growing concern of individuals, organizations and the government regarding the violation of privacy in the mining of their data by the existing data mining technology. As a result, a whole new body of research was introduced to allow for the mining of data, while at the same time prohibiting the leakage of any private and sensitive information. In this chapter, the authors introduce the readers to the field of privacy preserving data mining; they discuss the reasons that led to its inception, the most prominent research directions, as well as some important methodologies per direction. Following that, the authors focus their attention on very recently investigated methodologies for the offering of privacy during the mining of user mobility data. In the end of the chapter, they provide a roadmap along with potential future research directions both with respect to the field of privacy-aware mobility data mining and to privacy preserving data mining at large.

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