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ISI
2005
Springer

Data Distortion for Privacy Protection in a Terrorist Analysis System

14 years 5 months ago
Data Distortion for Privacy Protection in a Terrorist Analysis System
Data distortion is a critical component to preserve privacy in security-related data mining applications, such as in data miningbased terrorist analysis systems. We propose a sparsified Singular Value Decomposition (SVD) method for data distortion. We also put forth a few metrics to measure the difference between the distorted dataset and the original dataset. Our experimental results using synthetic and real world datasets show that the sparsified SVD method works well in preserving privacy as well as maintaining utility of the datasets.
Shuting Xu, Jun Zhang, Dianwei Han, Jie Wang
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where ISI
Authors Shuting Xu, Jun Zhang, Dianwei Han, Jie Wang
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