Corpus ID: 56895360

How to Achieve High Classification Accuracy with Just a Few Labels: A Semi-supervised Approach Using Sampled Packets

@article{Rezaei2019HowTA,
  title={How to Achieve High Classification Accuracy with Just a Few Labels: A Semi-supervised Approach Using Sampled Packets},
  author={Shahbaz Rezaei and Xin Liu},
  journal={ArXiv},
  year={2019},
  volume={abs/1812.09761}
}
  • Shahbaz Rezaei, Xin Liu
  • Published 2019
  • Computer Science
  • ArXiv
  • Network traffic classification, which has numerous applications from security to billing and network provisioning, has become a cornerstone of today's computer networks. Previous studies have developed traffic classification techniques using classical machine learning algorithms and deep learning methods when large quantities of labeled data are available. However, capturing large labeled datasets is a cumbersome and time-consuming process. In this paper, we propose a semi-supervised approach… CONTINUE READING
    10 Citations
    Multitask Learning for Network Traffic Classification
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    • 2020 29th International Conference on Computer Communications and Networks (ICCCN)
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