|
![]() |
|||
|
||||
OverviewData mining has emerged as a significant technology for gaining knowledge from vast quantities of data. However, concerns are growing that use of this technology can violate individual privacy. These concerns have led to a backlash against the technology, for example, a Data-Mining Moratorium Act introduced in the US Senate that would have banned all data-mining programs (including research and development) by the US Department of Defense. Privacy Preserving Data Mining provides a comprehensive overview of available approaches, techniques and open problems in privacy preserving data mining. This book demonstrates how these approaches can achieve data mining, while operating within legal and commercial restrictions that forbid release of data. Furthermore, this research crystallizes much of the underlying foundation, and inspires further research in the area. Privacy Preserving Data Mining' is designed for a professional audience composed of practitioners and researchers in industry. This volume is also suitable for graduate-level students in computer science. Full Product DetailsAuthor: Chris Clifton , Jaideep Vaidya , Michael ZhuPublisher: Springer Imprint: Springer ISBN: 9786610709526ISBN 10: 6610709521 Pages: 124 Publication Date: 01 January 2006 Audience: General/trade , General Format: Electronic book text Publisher's Status: Active Availability: Out of stock ![]() The supplier is temporarily out of stock of this item. It will be ordered for you on backorder and shipped when it becomes available. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |