@article{2275,
  author = {Honglin He},
  title = {A Network Traffic Classification Method Using Support Vector Machine with Feature Weighted-degree},
  journal = {Journal of Digital Information Management},
  year = {2017},
  volume = {15},
  number = {2},
  doi = {},
  url = {http://dline.info/fpaper/jdim/v15i2/jdimv15i2_3.pdf},
  abstract = {Currently, the network traffic classification
has two important problems, which are low accuracy and
high computation complexity. In order to solve these
problems, a novel network traffic classification method
using support vector machine with feature weighted-degree
(FWD-SVM) is proposed in this study. Our method can
efficiently reduce the influence on the sample distribution,
relative properties, and redundancy. Through reducing the
training time of traffic classification machine and the
predicting time of unknown samples,our method speeds
up computation performance. Using support vector
machine with feature weighted-degree, our method
improves the stability and the accuracy of classification.
The experimental results demonstrate that the proposed
method not only can greatly reduce the computation
complexity, but also has higher classified accuracy.},
}