Privacy preserving data mining

Author(s)

    • Vaidya, Jaideep
    • Clifton, Christopher W.
    • Zhu, Yu Michael

Bibliographic Information

Privacy preserving data mining

Jaideep Vaidya, Christopher W. Clifton, Yu Michael Zhu

(Advances in information security, 19)

Springer, c2006

Available at  / 10 libraries

Search this Book/Journal

Description and Table of Contents

Description

Privacy preserving data mining implies the "mining" of knowledge from distributed data without violating the privacy of the individual/corporations involved in contributing the data. This volume provides a comprehensive overview of available approaches, techniques and open problems in privacy preserving data mining. Crystallizing much of the underlying foundation, the book aims to inspire further research in this new and growing area. Privacy Preserving Data Mining is intended to be accessible to industry practitioners and policy makers, to help inform future decision making and legislation, and to serve as a useful technical reference.

Table of Contents

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.

by "Nielsen BookData"

Related Books: 1-1 of 1

Details

  • NCID
    BA75425435
  • ISBN
    • 0387258868
  • Country Code
    us
  • Title Language Code
    eng
  • Text Language Code
    eng
  • Place of Publication
    New York
  • Pages/Volumes
    120 p.
  • Size
    25 cm
  • Parent Bibliography ID
Page Top