A Novel Approach for Network Traffic Summarization

Abstract

Network traffic analysis is a process to infer patterns in communication. Reliance on computer network and increasing connectivity of these networks makes it a challenging task for the network managers to understand the nature of the traffic that is carried in their network. However, it is an important data analysis task, given the amount of network traffic generated. Summarization is a key data mining concept, which is considered as a solution for creating concise yet accurate summary of network traffic. In this paper, we propose a new definition of summary for network traffic which outperforms the existing state-of-the-art summarization techniques. Our approach is based on clustering algorithm which reduces the information loss incurred by the existing techniques. By analysing the traffic summarization results using most up to date evaluation metrics, we demonstrate that our approach achieves better summaries than others on benchmark KDD cup 1999 dataset and also on real life network traffic including simulated attacks.