|
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.
Essential Cell Biology: A Practical Approach Volume 2: Cell Function (Practical Approach Series, 262, etc.) Автор: John Davey, J. Michael Lord Год: 2003 |
Statistical bioinformatics Автор: Lee J.K. Год: 2010 |
Supply Chain Integration Автор: Thawatchai Jitpaiboon Год: 2010 |
Simulating natural phenomena for computer graphics Автор: Fedkiw R. Год: 2002 |
Computerized Data Acquisition and Analysis for the Life Sciences: A Hands-On Guide Автор: Young S.S. Год: 2001 |