Privacy-Preserving Data Mining : Models and Algorithms PDF
Edited by Charu C. Aggarwal, Philip S. Yu
Part of the Advances in Database Systems series
- Information
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.
Information
-
Download Now
- Format:PDF
- Publisher:Springer US
- Publication Date:10/06/2008
- Category:
- ISBN:9780387709925
Information
-
Download Now
- Format:PDF
- Publisher:Springer US
- Publication Date:10/06/2008
- Category:
- ISBN:9780387709925