Active Learning for Network Traffic Classification: A Technical Study

@article{Shahraki2022ActiveLF,
  title={Active Learning for Network Traffic Classification: A Technical Study},
  author={Amin Shahraki and Mahmoud Abbasi and Amirhosein Taherkordi and Anca Delia Jurcut},
  journal={IEEE Transactions on Cognitive Communications and Networking},
  year={2022},
  volume={8},
  pages={422-439}
}
Network Traffic Classification (NTC) has become an important feature in various network management operations, e.g., Quality of Service (QoS) provisioning and security services. Machine Learning (ML) algorithms as a popular approach for NTC can promise reasonable accuracy in classification and deal with encrypted traffic. However, ML-based NTC techniques suffer from the shortage of labeled traffic data which is the case in many real-world applications. This study investigates the applicability… 

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