Traffic classification describes the methods of classifying traffic by observing features passively in the traffic, and in line to particular classification goals. There might be some that only have a vulgar classification goal. For example, whether it is bulk transfer, peer to peer file sharing or transaction-orientated. Some others will set a finer-grained classification goal, for instance the exact number of application represented by the traffic. Traffic features included port number, application payload, temporal, packet size and the characteristic of the traffic. There are a vast range of methods to allocate Internet traffic including exact traffic, for instance port (computer networking) number, payload, heuristic or statistical machine learning.
Accurate network traffic classification is elementary to quite a few Internet activities, from security monitoring to accounting and from quality of service to providing operators with useful forecasts for long-term provisioning. Yet, classification schemes are extremely complex to operate accurately due to the shortage of available knowledge to the network. For example, the packet header related information is always insufficient to allow for an precise methodology. Consequently, the accuracy of any traditional method are between 50%-70%.