Pippy Search: Anomaly Traffic Clustering
Lili Yang, Jie Wang, Mansoor Ahmed Khuhro · 2015
Terrible network environment is damaging the critical infrastructure and the interests of internet users. In order to ensure the protection and resilience of attack, it is important to better analyze and observe network traffic for discovering anomaly. This paper presents a clustering algorithm by using network-layer and transport-layer statistical feature to classify anomaly traffic. Experiments with public datasets show the proposed algorithm has a significant effectiveness of traffic clustering quality.