Privacy-Preserving Data Mining Models and Algorithms /
Advances in hardware technology have increased the capability to store and record personal data about consumers and individuals. This has caused concerns that personal data may be used for a variety of intrusive or malicious purposes. Privacy Preserving Data Mining: Models and Algorithms proposes a...
Corporate Author: | |
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Other Authors: | , |
Format: | Electronic eBook |
Language: | English |
Published: |
Boston, MA :
Springer US,
2008.
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Series: | Advances in Database Systems,
34 |
Subjects: | |
Online Access: | Full Text via HEAL-Link |
Table of Contents:
- 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.