A gentle introduction for those new to the area, this book presents state-of-the-art information sharing and data integration methods that take into account privacy and data mining requirements. Real-life case studies illustrate the practical challenges of information sharing. The book addresses the privacy issues of relational, transaction, trajectory, social network, and textual data. The authors discuss the assumptions and desirable properties of privacy-preserving data publishing, evaluate various approaches to privacy-preserving data publishing, and explore the differences in privacy-preserving data publishing from related research areas. They also cover applications and future trends.

� propos de l?auteur:

Benjamin C. M. Fung is an assistant professor in the Concordia Institute for Information Systems Engineering at Concordia University in Montreal, Quebec. Dr. Fung is also a research scientist and the treasurer of the National Cyber-Forensics and Training Alliance Canada (NCFTA Canada).

Ke Wang is a professor in the School of Computing Science at Simon Fraser University in Burnaby, British Columbia.

Ada Wai-Chee Fu is an associate professor in the Department of Computer Science and Engineering at the Chinese University of Hong Kong.

Philip S. Yu is a professor in the Department of Computer Science and the Wexler Chair in Information and Technology at the University of Illinois at Chicago.

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Articles li�s � Introduction to Privacy-Preserving Data Publishing:...

Introduction to Privacy-Preserving Data Publishing: Concepts and Techniques (Chapman & Hall/CRC Data Mining and Knowledge Discovery)

Fung, Benjamin C.M.; Wang, Ke; Fu, Ada Wai-Chee; Yu, Philip S.

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