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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 U.S. Senate that would have banned all data-mining programs (including research and development) by the U.S. 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 Us Imprint: Springer Us ISBN: 9781280709524ISBN 10: 1280709529 Pages: 120 Publication Date: 01 January 2006 Audience: General/trade , General Format: Undefined Publisher's Status: Active Availability: Available To Order ![]() We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |