Hidden Markov model based P2P flow identification technique
To 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...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2012-06-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/1000-436X(2012)06-0055-09/ |
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| Summary: | To 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 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. |
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| ISSN: | 1000-436X |