cover

Secure Data Mining

Authors: Zhan, Justin, Matwin, Stan

  • Illustrates crypto based privacy and security aspects of data mining
  • Includes information on semantic security, for which the market has very little available research
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Buy this book

eBook $59.99
price for USA (gross)
  • The eBook version of this title will be available soon
  • Due: February 21, 2020
  • ISBN 978-0-387-87966-6
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Hardcover $79.99
price for USA
  • Customers within the U.S. and Canada please contact Customer Service at +1-800-777-4643, Latin America please contact us at +1-212-460-1500 (24 hours a day, 7 days a week).
  • Due: February 21, 2020
  • ISBN 978-0-387-87965-9
  • Free shipping for individuals worldwide
About this book

Data mining is a process to extract useful knowledge from large amounts of data. To conduct data mining, we often need to collect data. However, privacy concerns may prevent people from sharing the data and some types of information about the data. How we conduct data mining without breaching data privacy presents a challenge.

Secure Data Mining provides solutions to the problem of data mining without compromising data privacy. This professional book is designed for practitioners and researchers in industry, as well as a secondary textbook for advanced-level students in computer science.

Buy this book

eBook $59.99
price for USA (gross)
  • The eBook version of this title will be available soon
  • Due: February 21, 2020
  • ISBN 978-0-387-87966-6
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Hardcover $79.99
price for USA
  • Customers within the U.S. and Canada please contact Customer Service at +1-800-777-4643, Latin America please contact us at +1-212-460-1500 (24 hours a day, 7 days a week).
  • Due: February 21, 2020
  • ISBN 978-0-387-87965-9
  • Free shipping for individuals worldwide

Bibliographic Information

Bibliographic Information
Book Title
Secure Data Mining
Authors
Copyright
2020
Publisher
Springer US
Copyright Holder
Springer Science+Business Media, LLC, part of Springer Nature
eBook ISBN
978-0-387-87966-6
Hardcover ISBN
978-0-387-87965-9
Edition Number
1
Number of Illustrations
20 b/w illustrations
Topics