Dempster-Shafer for Anomaly Detection

Details Dempster-Shafer for Anomaly Detection Dempster-Shafer for Anomaly Detection

2008-03-11

arxiv.org/abs/0803.1568v1

Proceedings of the International Conference on Data Mining (DMIN 2006), pp 232-238, Las Vegas, USA 2006

Computer Science

Neural and Evolutionary Computing

Scientific paper

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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