Machine Learning Models for Feature Selection and Classification of Traffic Anomalies
Presenter
September 5, 2012
Keywords:
- Traffic problems
MSC:
- 90B20
Abstract
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.