Privacy-Preserving Data Mining : Models and Algorithms

Philip S. Yu

ISBN 10: 1441943714 / ISBN 13: 9781441943712

Verlag: Springer US, Springer US, 2010

Beschreibung

Druck auf Anfrage Neuware - Printed after ordering - 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. Bestandsnummer des Verkäufers 9781441943712

Bibliografische Details

Titel: Privacy-Preserving Data Mining : Models and ...

Verlag: Springer US, Springer US

Erscheinungsdatum: 2010

Einband: Taschenbuch

Zustand: Neu

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From the reviews:

"This book provides an exceptional summary of the state-of-the-art accomplishments in the area of privacy-preserving data mining, discussing the most important algorithms, models, and applications in each direction. The target audience includes researchers, graduate students, and practitioners who are interested in this area. ... I recommend this book to all readers interested in privacy-preserving data mining." (Aris Gkoulalas-Divanis, ACM Computing Reviews, October, 2008)