PCA算法在P2P加密流量识别中的研究与应用

Research and Application of Identifying Encrypted P2P Traffic with PCA

传统的应用层协议识别方法均从改进匹配算法的角度来提高识别率,但是随着P2P协议的发展,其特征呈现多维化的趋势,算法复杂度也随之提高。鉴于此,在对P2P流量的多维特征进行分析并提取后,采用主成分分析(PCA)算法将提取到的特征降维处理,并通过实验证明了该方法在网络流量识别上的可行性和有效性。

At present, improving matching algorithm is commonly used by traditional application layer protocol identification methods to raise identification rate, but with the development of P2P protocol, features are multi-dimensional, and algorithms are more complex too. In view of this, with the pretreatment by analyzing and extracting muhi-dimensional features of P2P traffic, Principal Component Analysis （PCA） algorithm is adopted to reduce the dimensions of features, and this strategy is approved feasible and effective through experiments.