Privacy-Preserving Data Mining

Models and Algorithms

514 Seiten, Taschenbuch

Kurzbeschreibung des Verlags

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.

 

• Reihe: Advances in Database Systems
• ISBN: 9781441943712
• Sprache: Englisch
• Erscheinungsdatum: 19.11.2010
• Genre: Informatik, EDV/Informatik
• Verlag: Springer US
• Herausgegeben von: Charu C. Aggarwal, Philip S. Yu