Privacy-Preserving Data Mining
Models and Algorithms
(Sprache: Englisch)
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...
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Produktinformationen zu „Privacy-Preserving Data Mining “
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.
Klappentext zu „Privacy-Preserving Data Mining “
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.
Inhaltsverzeichnis zu „Privacy-Preserving Data Mining “
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.
Bibliographische Angaben
- 2010, Softcover reprint of hardcover 1st ed. 2008., 514 Seiten, Maße: 23,5 cm, Kartoniert (TB), Englisch
- Herausgegeben:Aggarwal, Charu C.; Yu, Philip S
- Verlag: Springer
- ISBN-10: 1441943714
- ISBN-13: 9781441943712
Sprache:
Englisch
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