| Privacy-Preserving Data Mining: Models and Algorithms Contributor(s): Aggarwal, Charu C. (Editor), Yu, Philip S. (Editor) |
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ISBN: 1441943714 ISBN-13: 9781441943712 Publisher: Springer OUR PRICE: $208.99 Product Type: Paperback - Other Formats Published: December 2010 |
| Additional Information |
| BISAC Categories: - Computers | Security - Networking - Computers | Security - Cryptography - Computers | Databases - Data Mining |
| Dewey: 005.74 |
| Series: Advances in Database Systems |
| Physical Information: 1.08" H x 6.14" W x 9.21" (1.64 lbs) 514 pages |
| Descriptions, Reviews, Etc. |
| Publisher 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.
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