Abstract

Internet traffic classification is valuable mechanism in the direction of traffic detection and monitoring. Even though several classification approaches were proposed by the research community, there still exist many open problems on Internet traffic classification. The hybrid classifier is a classifier which combines more than one classification method to identify the Internet traffic. Using only one method to classify Internet traffic poses many risks. Therefore, this paper proposed a hybrid classifier (HC) system to identify internet traffic. HC is based on two common classification methods, i.e. port-base and ML-base. CH was able to perform an online classification since it able to identify the live Internet traffic at the same time as when the traffic was generated. HC was used to classify three common Internet applications classes i.e. web, WhatsApp, and Twitter. HC is produces more than 90% classification accuracy which is higher when compared with other individual classifiers.