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Privacy-Preserving Data Mining

Models and Algorithms

Gebonden Engels 2008 2008e druk 9780387709918
Verwachte levertijd ongeveer 9 werkdagen

Samenvatting

Advances in hardware technology have increased the capability to store and record personal data. This has caused concerns that personal data may be abused. This book proposes a number of techniques to perform the data mining tasks in a privacy-preserving way. 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 of a particular topic in privacy. The book is designed for researchers, professors, and advanced-level students in computer science, but is also suitable for practitioners in industry.

Specificaties

ISBN13:9780387709918
Taal:Engels
Bindwijze:gebonden
Aantal pagina's:514
Uitgever:Springer US
Druk:2008

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Inhoudsopgave

An Introduction to Privacy-Preserving Data Mining.- A General Survey of Privacy-Preserving Data Mining Models and Algorithms.- A Survey of Inference Control Methods for Privacy-Preserving Data Mining.- Measures of Anonymity.- k-Anonymous Data Mining: A Survey.- A Survey of Randomization Methods for Privacy-Preserving Data Mining.- A Survey of Multiplicative Perturbation for Privacy-Preserving Data Mining.- A Survey of Quantification of Privacy Preserving Data Mining Algorithms.- A Survey of Utility-based Privacy-Preserving Data Transformation Methods.- Mining Association Rules under Privacy Constraints.- A Survey of Association Rule Hiding Methods for Privacy.- A Survey of Statistical Approaches to Preserving Confidentiality of Contingency Table Entries.- A Survey of Privacy-Preserving Methods Across Horizontally Partitioned Data.- A Survey of Privacy-Preserving Methods Across Vertically Partitioned Data.- A Survey of Attack Techniques on Privacy-Preserving Data Perturbation Methods.- Private Data Analysis via Output Perturbation.- A Survey of Query Auditing Techniques for Data Privacy.- Privacy and the Dimensionality Curse.- Personalized Privacy Preservation.- Privacy-Preserving Data Stream Classification.

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