Privacy Preserving Data Mining

✍ Scribed by Jaideep Vaidya, Yu Michael Zhu, Christopher W. Clifton (auth.)

• Publisher: Springer US
• Year: 2006
• Tongue: English
• Leaves: 123
• Series: Advances in Information Security 19
• Edition: 1
• Category: Library

✦ 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.

✦ Table of Contents

Front Matter....Pages i-ix
Privacy and Data Mining....Pages 1-5
What is Privacy?....Pages 7-15
Solution Approaches / Problems....Pages 17-27
Predictive Modeling for Classification....Pages 29-52
Predictive Modeling for Regression....Pages 53-69
Finding Patterns and Rules (Association Rules)....Pages 71-83
Descriptive Modeling (Clustering, Outlier Detection)....Pages 85-111
Future Research - Problems remaining....Pages 113-114
Back Matter....Pages 115-121

✦ Subjects

Data Mining and Knowledge Discovery; Database Management; Data Structures, Cryptology and Information Theory; Data Encryption; Information Storage and Retrieval; Computer Communication Networks