Anomaly Detection Using the Dempster-Shafer Method

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Anomaly Detection Using the Dempster-Shafer Method
In this paper, we implement an anomaly detection system using the Dempster-Shafer method. Using two standard benchmark problems we show that by combining multiple signals it is possible to achieve better results than by using a single signal. We further show that by applying this approach to a real-world email dataset the algorithm works for email worm detection. Dempster-Shafer can be a promising method for anomaly detection problems with multiple features (data sources), and two or more classes.
Qi Chen, Uwe Aickelin
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2006
Where DMIN
Authors Qi Chen, Uwe Aickelin
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