Anomaly detection for packet-based networks

摘要

Disclosed herein is an anomaly detection method for a packet-based network which includes several network resources, also called network-related software objects. The method includes monitoring the network resources of the packet-based network, ordering the monitored network resources according to a given ordering criterion, and detecting an anomaly in the packet-based network based on the ordered network resources. In particular, detecting an anomaly includes forming a detection feature vector based on the ordered network resources, and feeding the detection feature vector to a machine learning system configured to detect an anomaly in the packet-based network based on the detection feature vector. The detection feature vector includes detection feature items related to corresponding monitored network resources, and arranged in the detection feature vector depending on the ordering of the corresponding monitored network resources. Conveniently, the machine learning system is a one-class classifier, preferably a one-class Support Vector Machine (OC-SVM).