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Machine Learning Models for Feature Selection and Classification of Traffic Anomalies

Wednesday, September 5, 2012 - 10:00am - 11:00am
Lind 305
Ljiljana Trajkovic (Simon Fraser University)
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.
MSC Code: 
90B20
Keywords: