E-Book, Englisch, 514 Seiten
Privacy-Preserving Data Mining
1. Auflage 2008
ISBN: 978-0-387-70992-5
Verlag: Springer-Verlag
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)
Models and Algorithms
E-Book, Englisch, 514 Seiten
ISBN: 978-0-387-70992-5
Verlag: Springer-Verlag
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)
Advances in hardware technology have increased the capability to store and record personal data about consumers and individuals, causing concerns that personal data may be used for a variety of intrusive or malicious purposes.
Privacy-Preserving Data Mining: Models and Algorithms proposes a number of techniques to perform the data mining tasks in a privacy-preserving way. These techniques generally fall into the following categories: data modification techniques, cryptographic methods and protocols for data sharing, statistical techniques for disclosure and inference control, query auditing methods, randomization and perturbation-based techniques.
This edited volume contains surveys by distinguished researchers in the privacy field. Each survey includes the key research content as well as future research directions.
Privacy-Preserving Data Mining: Models and Algorithms is designed for researchers, professors, and advanced-level students in computer science, and is also suitable for industry practitioners.
