Product 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.
Product Details
Hardcover: 514 pages
Publisher: Springer; 1 edition (July 7, 2008)
Language: English
ISBN-10: 0387709916
ISBN-13: 978-0387709918
Product Dimensions: 9.3 x 6 x 1 inches
Hardcover: 514 pages
Publisher: Springer; 1 edition (July 7, 2008)
Language: English
ISBN-10: 0387709916
ISBN-13: 978-0387709918
Product Dimensions: 9.3 x 6 x 1 inches
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