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COMSNETS
2012
183views more  COMSNETS 2012»
13 years 5 months ago
Effects of network trace sampling methods on privacy and utility metrics
—Researchers choosing to share wireless-network traces with colleagues must first anonymize sensitive information, trading off the removal of information in the interest of iden...
Phil Fazio, Keren Tan, David Kotz
COMSWARE
2006
IEEE
15 years 4 months ago
Utilizing network features for privacy violation detection
Privacy, its violations and techniques to circumvent privacy violation have grabbed the centre-stage of both academia and industry in recent months. Corporations worldwide have be...
Jaijit Bhattacharya, Rajanish Dass, Vishal Kapoor,...
KDD
2004
ACM
159views Data Mining» more  KDD 2004»
15 years 3 months ago
Optimal randomization for privacy preserving data mining
Randomization is an economical and efficient approach for privacy preserving data mining (PPDM). In order to guarantee the performance of data mining and the protection of individ...
Michael Yu Zhu, Lei Liu
TDP
2008
160views more  TDP 2008»
14 years 10 months ago
Enhanced P-Sensitive K-Anonymity Models for Privacy Preserving Data Publishing
Publishing data for analysis from a micro data table containing sensitive attributes, while maintaining individual privacy, is a problem of increasing significance today. The k-ano...
Xiaoxun Sun, Hua Wang, Jiuyong Li, Traian Marius T...
MADNES
2005
Springer
15 years 3 months ago
Distributed Data Mining Protocols for Privacy: A Review of Some Recent Results
With the rapid advance of the Internet, a large amount of sensitive data is collected, stored, and processed by different parties. Data mining is a powerful tool that can extract ...
Rebecca N. Wright, Zhiqiang Yang, Sheng Zhong