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.

• Type: Conference
• Year: 2006
• Where: DMIN
• Authors: Qi Chen, Uwe Aickelin
• Keywords: Anomaly Detection, DMIN 2006, DMIN 2007, Email Worm Detection, Standard Benchmark Problems