Privacy Preserving Data Mining

Author:   Chris Clifton ,  Jaideep Vaidya ,  Michael Zhu
Publisher:   Springer Us
ISBN:  

9781280709524


Pages:   120
Publication Date:   01 January 2006
Format:   Undefined
Availability:   Available To Order   Availability explained
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Privacy Preserving Data Mining


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Overview

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.

Full Product Details

Author:   Chris Clifton ,  Jaideep Vaidya ,  Michael Zhu
Publisher:   Springer Us
Imprint:   Springer Us
ISBN:  

9781280709524


ISBN 10:   1280709529
Pages:   120
Publication Date:   01 January 2006
Audience:   General/trade ,  General
Format:   Undefined
Publisher's Status:   Active
Availability:   Available To Order   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

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