Unknown P2P Traffic Identification Method Based on Frequent Item Mining
Ting Pan · Jisuanji gongcheng · 2009
A novel frequent item mining algorithm based on multi-dimentsional clustering is proposed,which uses clustering theory to mine significant flow and its rules automatically in network.On basis of this,P2P suspected identification is conducted to these flows.Combined with application layer feature recognition technology,highly suspected P2P significant flow is filtered,and unknown P2P traffic detection is implemented.Experimental results show this method is effective.