文献类型：期刊文献

英文题名：Novel model for detecting P2P downloading based on data mining

作者：Wang, Xiu-Ying; Shao, Zhi-Qing; Chen, Li-Qiong

机构：[1] School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China; [2] Shanghai Xinqiao Vocational and Technical College, Shanghai 200237, China

年份：2008

卷号：34

期号：4

起止页码：558

外文期刊名：Huadong Ligong Daxue Xuebao /Journal of East China University of Science and Technology

收录：EI(收录号：20083911603597)

语种：英文

摘要：A novel real-time model to detect P2P downloading is presented. Firstly, features are extracted by using Apriori algorithm, and the dataset is offline. Secondly, P2P users are detected by clustering algorithm with the extracted features. The clustering is based on similarity among records. The alarm will be triggered, if the statistic value is greater than a threshold, and the dataset is online. There are three characteristics in the proposed model. The first is unsupervised approach. The second is real-time. The third is that the firewall is associated to cut down the connection between P2P user and Internet.