Clustering network traffic utilization - Mohd Khairudin, Nazli; Muda, Zaiton; Mustapha, Aida; Nagarathinam, Yogeswaran; Salleh, Mohd. Sidek (Praise Worthy Prize, 2013)
Classification of network traffic using distinctive characteristic application is not ideal for P2P and HTTP protocols. This is for the case when a user intercepts the application from other proxy or dynamic port, then the bytes utilization can be manipulated. In this paper, we present a clustering approach for network traffic classification using information from one particular port. The clustering experiments were conducted using three different clustering algorithms, which are K-Means, DBScan and AutoClass. The analysis discussed on the quality of resulting clusters from all the algorithms.