A P2P Flow Identification Model Based on Bayesian Network

The fundamental work of managing P2P flow is to identify various P2P flows. In this essay, we constitute a uniform P2P flow identification model-UFIM, and analyze different identification methods. An idea to describe UFIM abstractly utilizing Bayesian network model is advanced. We make 6 measurements to denote identification performance. The contrasting result in theory analysis and experiments shows that UFIM can denote various type of P2P flow identification method abstractly. All these works establish the base of giving new identification method further.