Features
- Cover Type: Hard Cover with 121 pages
- Published by: Springer
- Edition: 1st Edition November 29, 2005
- Written in: English
- ISBN 10 Number: 0387258868
- ISBN 13 Number: 978-0387258867
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Book Dimensions:
9.2 x 6.2 x 0.5 inches
- Weighs: 12.6 ounces
Product Description
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.
Reader ReviewsPrivacy is very important for any data manipulation and data mining gives the feeling to the large public to have the power to discover very private things in data. And it's true. The authors try to find some methods to do data mining in avoiding of having access to the private part (too much private part) of these data but in staying able to learn something about individuals behind. It's not easy and very interesting to learn. Of course the applications are limited because very often data mining has for purpose to score a particular individual. To read and to think about...
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