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Privacy Preserving Data Mining

  • Kartonierter Einband
  • 122 Seiten
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Data mining has emerged as a significant technology for gaining knowledge from vast quantities of data. However, concerns are grow... Weiterlesen
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Beschreibung

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.



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



Inhalt
Privacy and Data Mining.- What is Privacy?.- Solution Approaches / Problems.- Predictive Modeling for Classification.- Predictive Modeling for Regression.- Finding Patterns and Rules (Association Rules).- Descriptive Modeling (Clustering, Outlier Detection).- Future Research - Problems remaining.

Produktinformationen

Titel: Privacy Preserving Data Mining
Autor:
EAN: 9781441938473
ISBN: 978-1-4419-3847-3
Format: Kartonierter Einband
Herausgeber: Springer, Berlin
Genre: Informatik
Anzahl Seiten: 122
Gewicht: 211g
Größe: H10mm x B234mm x T180mm
Jahr: 2010
Auflage: Softcover reprint of hardcover 1st ed. 2006

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