Packet classification using the Hidden Markov Model

In the last decade, traffic classification has been the most interesting field for the majority of network searchers, and this behavior is caused by its importance, so many successful results have already improved reached. In this way, we present our method of packet classification which is based on the Hidden Markov Model (HMM); as an HMM states we are interested to the Flags bits of a TCP packet, and as an HMM observations we were convinced that we should focus on a packet property that didn´t depend on the payload information to avoid the encryption problem, so the right alternative was the distribution of the packet size for each state of our HMM. This process has been verified and validated by several applications like: Steaming video over HTTP (youtube.com, dailymotion.com, justin.tv), peer-to-peer video streaming, File transfer protocol (FTP). Based on the related woks in this field, our method has given us convenient results comparing to old works.