摘要
目前,已有多种方法可高效准确地完成对P2P流量的粗识别,但对P2P流量的精细化识别研究较少。该文首次将近邻传播(Affinity Propagation,AP)算法引入该领域,在Hi-WAP算法的基础上融合半监督聚类思想提出了一种基于分层加权半监督近邻传播(Hierarchical Weighted Semi-supervised AP,Hi-WSAP)算法的P2P流量精细化识别方法。该方法仅利用10个可快速计算获取的网络流特征对P2P流量按应用进行半监督聚类。两组数据集下的实验结果表明,该方法识别准确率高,时间复杂度低,为P2P流量的实时精细化识别提供了一种实现思路。
Various methods are capable of classifying Peer to Peer （P2P） traffic in coarse grained way efficiently and accurately. However, few papers focus on the fine grained identification of P2P traffic. Affinity Propagation （AP） algorithm is brought to P2P traffic identification field for the first time and a novel method of identifying P2P traffic finely based on Hierarchical Weighted Semi-supervised AP （Hi-WSAP） algorithm is proposed, which is on the foundation of the Hi-WAP algorithm and absorbs the semi-supervised thought. The proposed method identifies P2P traffic in semi-supervised way by application employing only 10 fast computed traffic features. Experimental results using two datasets show this method achieves high identification accuracy and low time complexity, which provides a path to finely identify P2P traffic in real-time.
出处
《电子与信息学报》
EI
CSCD
北大核心
2012年第7期1709-1714,共6页
Journal of Electronics & Information Technology
基金
国家科技支撑计划(2011BAH19B01)
国家973计划项目(2012CB315901)资助课题
关键词
P2P
近邻传播
精细化识别
半监督聚类
Peer to Peer （P2P）
Affinity Propagation （AP）
Fine grained identification
Semi-supervised clustering
