Privacy-Preserving Data Mining: Models and Algorithms (Advances in Database Systems)

By Ton Kloks and Mingyu Xiao

Advances in hardware technology have increased the capability to store and record personal data about consumers and individuals. This has caused concerns that personal data may be used for a variety of intrusive or malicious purposes. This book proposes a number of techniques to perform the data mining tasks in a privacy-preserving way. This edited volume contains surveys by distinguished researchers in the privacy field. The survey information included with each chapter is unique in terms of its focus on introducing the different topics more comprehensively. Key advances in privacy that have appeared only in the past three years are covered. The book is designed for researchers, professors, and advanced-level students in computer science. It is also suitable for practitioners in industry.

• Format: Hardcover
• Language: English
• ISBN: 0387709916
• ISBN13: 9780387709918
• Release Date: July 2008
• Publisher: Springer
• Length: 514 Pages
• Weight: 1.95 lbs.
• Dimensions: 1.2" x 6.1" x 9.3"