Machine Learning Models for Feature Selection and Classification of Traffic Anomalies
Wednesday, September 5, 2012 - 10:00am - 11:00am
- N. Al-Rousan, S. Haeri, and Lj. Trajkovic, "Feature selection for classification of BGP anomalies using Bayesian models," in Proc. ICMLC 2012, Xi'an, China, July 2012.
- N. Al-Rousan and Lj. Trajkovic, "Machine learning models for classification of BGP anomalies," in Proc. IEEE Conference on High Performance Switching and Routing, HPSR 2012, Belgrade, Serbia, June 2012, pp. 103-108.
Traffic anomalies in communication networks greatly degrade network performance. In this talk, I will survey statistical and machine learning techniques that are used to classify and detect network anomalies such as Internet worms that affect performance of routing protocols. Various classification features are used to design anomaly detection mechanisms. They are used to classify test datasets and identify the correct anomaly types.