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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- About this book
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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.
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Secure Data Mining
- Authors
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- Justin Zhan
- Stan Matwin
- 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
*immediately available upon purchase as print book shipments may be delayed due to the COVID-19 crisis. ebook access is temporary and does not include ownership of the ebook. Only valid for books with an ebook version. Springer Reference Works are not included.
