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Privacy Preserving Data MiningPrivacy Preserving Data Mining

Privacy Preserving Data Mining

Chris Clifton, Jaideep Vaidya, Michael Zhu

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.

Details

OL Work ID
OL16924577W

Subjects

Data encryption (Computer science)Information storage and retrieval systemsDatabase managementComputer networksComputer network architecturesData structures (Computer science)Data miningData protectionDatabase securityComputer scienceComputer Communication NetworksData Mining and Knowledge DiscoveryCryptology and Information Theory Data StructuresData EncryptionInformation Storage and Retrieval

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