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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: Jaideep Vaidya , Christopher W. Clifton , Yu Michael ZhuPublisher: Springer-Verlag New York Inc. Imprint: Springer-Verlag New York Inc. Edition: 2006 ed. Volume: 19 Dimensions: Width: 15.50cm , Height: 0.90cm , Length: 23.50cm Weight: 0.810kg ISBN: 9780387258867ISBN 10: 0387258868 Pages: 122 Publication Date: 29 November 2005 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: In Print ![]() This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |