A semi-supervised clustering algorithm for real network traffic with concept drift

2019 2nd International Conference on Advanced Materials, Intelligent Manufacturing and Automation

Hua, Qu^1 ; Jie, Jiang^1 ; Jihong, Zhao^1^2 ; Yanpeng, Zhang^1

Xi'An Jiaotong University, Shaanxi Xi'an, China^1

Xi'An University of Posts and Telecommunications, Shaanxi Xi'an, China^2

关键词: Concept drifts;    Dynamic network;    Impact of noise;    Real networks;    Semi-supervised clustering algorithms;    Simulation demonstrate;    Static networks;    Traffic classification;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/569/5/052045/pdf
DOI  :  10.1088/1757-899X/569/5/052045

来源: IOP

【 摘 要 】

Traffic classification has been widely applied for networking. Previous works paid much attention to static network traffic. In this paper, we propose a new strategy for the semi-supervised clustering algorithm to deal the concept drift in a dynamic network, as well as updating the model incrementally. Moreover, our algorithm can find new clusters and reduce the impact of noises. The results of simulation demonstrate the effectiveness of semi-supervised clustering algorithm.