Privacy-Preserving Data Mining :Models and Algorithms - Advances in Database Systems
Privacy-Preserving Data Mining :Models and Algorithms - Advances in Database Systems
hardback
Published:
7 July, 2008
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Description
Advances in hardware technology have increased the capability to store and record personal data about consumers and individuals, causing concerns that personal data may be used for a variety of intrusive or malicious purposes.
Privacy-Preserving Data Mining: Models and Algorithms proposes a number of techniques to perform the data mining tasks in a privacy-preserving way. These techniques generally fall into the following categories: data modification techniques, cryptographic methods and protocols for data sharing, statistical techniques for disclosure and inference control, query auditing methods, randomization and perturbation-based techniques.
This edited volume contains surveys by distinguished researchers in the privacy field. Each survey includes the key research content as well as future research directions.
Privacy-Preserving Data Mining: Models and Algorithms is designed for researchers, professors, and advanced-level students in computer science, and is also suitable for industry practitioners.
More Details
| Type | Book |
|---|---|
| ISBN13 | 9780387709918 |
| ISBN10 | 0387709916 |
| Number Of Pages | 514 |
| Item Weight | 1000 g |
| Publisher / Reseller | Springer-Verlag New York Inc. |
| Format | hardback |
| Edition | 2008 ed. |
Media Reviews
From the reviews:
"This book provides an exceptional summary of the state-of-the-art accomplishments in the area of privacy-preserving data mining, discussing the most important algorithms, models, and applications in each direction. The target audience includes researchers, graduate students, and practitioners who are interested in this area. … I recommend this book to all readers interested in privacy-preserving data mining." (Aris Gkoulalas-Divanis, ACM Computing Reviews, October, 2008)