A novel P2P traffic identification model based on machine learning

作者：Xu He^*; Wang Suoping; Wang Ruchuan

来源：2nd International Conference on Information Science and Engineering, ICISE2010, 2010-12-04 to 2010-12-06.

DOI：10.1109/ICISE.2010.5691674

• 10-fold cross-validation
• Extracting features
• Feature selection
• Feature selection algorithm
• Flow attributes
• Flow identification
• Identification model
• Machine learning
• On-machines
• P2P
• P2p traffic identification

P2P traffic identification model based on machine learning is proposed. The FCBF(Fast Correlation-Based Filter) feature selection algorithm is used to select the P2P flow attribute features subset. A P2P flows identification model is built based on decision tree and FCBF. 10-fold cross-validation method is used to validate the proposed model. Experimental results show that the method of P2P traffic identification based on decision tree is feasible and the FCBF method is a useful method for extracting features from P2P flows.

• 出版日期2010
• 单位南京邮电大学