Method and apparatus for whole-network anomaly diagnosis and method to detect and classify network anomalies using traffic feature distributions

摘要

To improve network reliability and management in today's high-speed communication networks, we propose an intelligent system using adaptive statistical approaches. The system learns the normal behavior of the network. Deviations from the norm are detected and the information is combined in the probabilistic framework of a Bayesian network. The proposed system is thereby able to detect unknown or unseen faults. As demonstrated on real network data, this method can detect abnormal behavior before a fault actually occurs, giving the network management system (human or automated) the ability to avoid a potentially serious problem.

主权项

1. A method for detecting anomalies in network traffic, the method comprising:
during at least one training interval, collecting network traffic data comprising data from N network sources at a plurality of time periods t, where N>1; assigning, by a processor, the network traffic data collected during the at least one training interval from the N network sources to dimensions of an r-dimensional subspace, wherein 0