An Analysis of real-time network traffic for identification of browser and application of user using clustering algorithm

Abstract

The Internet is drastically becoming part of our life as well as work. Every aspect of life is somehow associated with Internet due to which communication and technology needs to be getting advanced day by day. With the affluent usage of encrypted network data, its classification has been predominantly accepted these days. The Classification of network traffic can be defined as the procedure of identification and analysis of application and protocol in the network. It has power to manage and solve different types of problem related to network. It can also provide network security by blocking the malicious traffic. This shows a challenge for measurement of traffic, especially for analysis method which are basically dependent on the types of traffic present in the network. In this paper we analysed real time traffic data of educational institute to identify browser and application of user using clustering algorithm basically KMeans. KMeans is basically the unsupervised Machine Learning algorithm.