Privacy Preserving Data Mining

Jaideep Vaidya

ISBN 10: 0387258868 / ISBN 13: 9780387258867

Published by Springer Us Nov 2005, 2005

About this Item

Neuware - Data 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.

Seller Inventory # 9780387258867

Bibliographic Details

• Title: Privacy Preserving Data Mining
• Publisher: Springer Us Nov 2005
• Publication Date: 2005
• Language: English
• ISBN 10: 0387258868
• ISBN 13: 9780387258867
• Binding: Buch
• Condition: Neu

About this title

Synopsis

Data 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.