摘要
文中针对P2P流量识别中流量特征向量选择的问题进行了研究,提出了一种基于单因素方差分析的P2P流量特征向量优化算法。该算法将统计学中单因素方差分析的方法引入P2P流量特征选取中,能够从高维的特征向量中选择出具有显著性作用的低维特征向量,从而实现P2P流特征向量的优化。实验结果表明,文中提出的方法可以在显著地提高P2P流量识别的效率的同时,将P2P流量识别准确率保持在一个可接受的范围内,为P2P流量识别的进一步研究提供了铺垫。
To acquire optimized feature of P2P flow,proposed a feature section method based on one-way analysis of variance.One-way analysis of variance in statistics,which can choose the most obvious factors from the high dimensional feature vector,was introduced to feature section.Experiment results demonstrate that with the use of the method efficiency of the P2P traffic identification is improved obviously and accuracy of P2P traffic identification is kept within acceptable limits.It is a setup for farther research.
出处
《计算机技术与发展》
2012年第4期101-103,107,共4页
Computer Technology and Development
基金
国家自然科学基金(61003237)
江苏省普通高校自然科学研究资助项目(10KJB510018)