A New P2P Traffic Identification Methodology Based on Flow Statistics

摘要：

Nowadays P2P traffic consumes a great amount of network bandwidth which brings many difficulties to network management. In order to accurately identify P2P traffic, this paper proposes a methodology based on flow statistics. At first it quickly eliminates those flow features irrelevant to class by the ReliefF algorithm, then from the rest features it uses a wrapper method combined genetic algorithm with support vector machine to select flow features and optimize the parameters of support vector machine model, and finally it outputs the best flow feature set and the optimized support vector machine model. The experimental results indicate that this methodology can achieve improved accuracy with fewer flow features.

关键词： P2P Traffic Identification Flow Statistics ReliefF Support Vector Machine Genetic Algorithm Feature Selection

作者: HuiLin Chu HongBo Yi XingMing Zhang

作者单位: National Digital Switch System Engineering & Technological R & D Center 450002 Zhengzhou, Henan, P.R. China

会议类型: 国际会议

会议名称: 2011 2nd International Conference on Data Storage and Data Engineering(DSDE 2011)(2011年第二届数据存储与数据工程国际会议)

会议地点: 西安

会议语种:英文

页码: 277-281

在线出版日期: 2011-05-13（万方平台首次上网日期，不代表论文的发表时间）