- STAFF PICKS
- GIFTS + GIFT CARDS
- SELL BOOKS
- FIND A STORE
New Trade Paper
Ships in 1 to 3 days
available for shipping or prepaid pickup only
Available for In-store Pickup
in 7 to 12 days
This title in other editions
Other titles in the Advances in Database Systems series:
Advances in Database Systems #34: Privacy-Preserving Data Mining: Models and Algorithmsby Charu C. Aggarwal
Synopses & Reviews
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 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 also 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. Privacy Preserving Data Mining: Models and Algorithms is designed for researchers, professors, and advanced-level students in computer science. This book is also suitable for practitioners in industry.
This book proposes a number of techniques to perform data mining tasks in a privacy-preserving way. The survey information included with each chapter is unique in terms of its focus on introducing the different topics more comprehensively.
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.- 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.- Index.
What Our Readers Are Saying