Overview
- First book on privacy preserving data mining - a real application of secure computation
- Written for researchers who wish to enter the field and need to know the state of the art methods for developing algorithms, and how to "prove" privacy
- Also intended for practitioners who need advice on privacy-preserving data mining applications, how to apply it, and what to watch out for
- Includes supplementary material: sn.pub/extras
Part of the book series: Advances in Information Security (ADIS, volume 19)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
About this book
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.
Similar content being viewed by others
Keywords
Table of contents (8 chapters)
-
Front Matter
-
Back Matter
Authors and Affiliations
Bibliographic Information
Book Title: Privacy Preserving Data Mining
Authors: Jaideep Vaidya, Yu Michael Zhu, Christopher W. Clifton
Series Title: Advances in Information Security
DOI: https://doi.org/10.1007/978-0-387-29489-6
Publisher: Springer New York, NY
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag US 2006
Hardcover ISBN: 978-0-387-25886-7Published: 29 November 2005
Softcover ISBN: 978-1-4419-3847-3Published: 19 November 2010
eBook ISBN: 978-0-387-29489-6Published: 28 September 2006
Series ISSN: 1568-2633
Series E-ISSN: 2512-2193
Edition Number: 1
Number of Pages: X, 122
Number of Illustrations: 20 b/w illustrations
Topics: Data Mining and Knowledge Discovery, Database Management, Data Structures and Information Theory, Cryptology, Information Storage and Retrieval, Computer Communication Networks