ANOMALY ANALYSIS AND IDENTIFICATION OF BACKBONE NETWORK BASED ON SKETCH AND REGULARITY DISTRIBUTION
Lin Luo · Xitong kexue yu shuxue · 2015
With the rapid development and the rising complexity of communication systems and networks,the threats from malicious attacks,worms,DDoS attacks also grow.How to detect the anomalies of the network traffic timely and accurately becomes an important issue.We propose a novel method based on the combining sketch and Lipschitz regularity distribution of backbone network traffic to reveal the anomalies.In this paper,our approach can not only locate time points that anomalies occurred and track the IP addresses of anomalies effectively on backbone network traffic,but also identify the anomalies by analyzing the entropy of source IP addresses.Analysis based on simulation experiments demonstrates that the method has very good performance on detection and traceability.