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Database/SQL Privacy Preserving Data Mining: Models and Algorithms

Posted on 2010-03-27




Name:Database/SQL Privacy Preserving Data Mining: Models and Algorithms
ASIN/ISBN:0387709916
Language:English
File size:4 Mb
   Database/SQL Privacy Preserving Data Mining: Models and Algorithms

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Springer | 2008-06-20 | ISBN: 0387709916 | 535 pages | PDF | 4 MB 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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