Hidden Markov model based P2P flow identification technique

Hidden Markov model based P2P flow identification technique

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To echofix spring reverb identify various P2P flows accurately in real-time,a hidden Markov model(HMM)based P2P flow identification technique was proposed.This approach made use of packet size,inter-arrival time and arrival order to construct flow identification model,in which discrete random variable was used to depict the characteristics of HMM state.A framework called HMM-FIA was proposed,which could identify various P2P flows simultaneously.Meanwhile,the algorithm for selecting the number of HMM state was designed.

In a controllable experimental circumstance in the campus network,HMM-FIA was utilized to identify P2P flows and was compared with other identification methods.The results show that discrete random variable click here can decrease the model constructing time and improve the time-cost and accuracy in identifying unknown flows,HMM-FIA can correctly identify the packet flows produced by various P2P protocols and it can be adaptive to different network circumstance.