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/ |
| _version_ | 1848790440294219776 |
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| author | Chen, Qi Aickelin, Uwe |
| author_facet | Chen, Qi Aickelin, Uwe |
| author_sort | Chen, Qi |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T18:12:39Z |
| format | Conference or Workshop Item |
| id | nottingham-596 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:12:39Z |
| publishDate | 2006 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-5962020-05-04T20:29:46Z https://eprints.nottingham.ac.uk/596/ Dempster-Shafer for Anomaly Detection Chen, Qi Aickelin, Uwe 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. 2006 Conference or Workshop Item PeerReviewed Chen, Qi and Aickelin, Uwe (2006) Dempster-Shafer for Anomaly Detection. In: Proceedings of the International Conference on Data Mining (DMIN 2006), Las Vegas, USA. |
| spellingShingle | Chen, Qi Aickelin, Uwe Dempster-Shafer for Anomaly Detection |
| title | Dempster-Shafer for Anomaly Detection |
| title_full | Dempster-Shafer for Anomaly Detection |
| title_fullStr | Dempster-Shafer for Anomaly Detection |
| title_full_unstemmed | Dempster-Shafer for Anomaly Detection |
| title_short | Dempster-Shafer for Anomaly Detection |
| title_sort | dempster-shafer for anomaly detection |
| url | https://eprints.nottingham.ac.uk/596/ |