Dempster-Shafer for Anomaly Detection
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-...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Published: |
2006
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| Online Access: | https://eprints.nottingham.ac.uk/596/ |
| Summary: | 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. |
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