Privacy-preserving outlier detection

被引：34
|
作者：
Vaidya, J [1 ]
Clifton, C [1 ]
机构：
[1] Rutgers State Univ, Newark, NJ 07102 USA
来源：
FOURTH IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS | 2004年
关键词：
D O I：
10.1109/ICDM.2004.10081
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Outlier detection can lead to the discovery of truly unexpected knowledge in many areas such as electronic commerce, credit card fraud and especially national security. We look at the problem of finding outliers in large distributed databases where privacy/security concerns restrict the sharing of data. Both homogeneous and heterogeneous distribution of data is considered. We propose techniques to detect outliers in such scenarios while giving formal guarantees on the amount of information disclosed.
引用
收藏
页码：233 / 240
页数：8
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