Flow-MAE: Leveraging Masked AutoEncoder for Accurate, Efficient and Robust Malicious Traffic Classification

Zijun Hang, Yuliang Lu, YongJie Wang, Yi Xie. Flow-MAE: Leveraging Masked AutoEncoder for Accurate, Efficient and Robust Malicious Traffic Classification. In Proceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses, RAID 2023, Hong Kong, China, October 16-18, 2023. pages 297-314, ACM, 2023. [doi]

@inproceedings{HangLWX23,
  title = {Flow-MAE: Leveraging Masked AutoEncoder for Accurate, Efficient and Robust Malicious Traffic Classification},
  author = {Zijun Hang and Yuliang Lu and YongJie Wang and Yi Xie},
  year = {2023},
  doi = {10.1145/3607199.3607206},
  url = {https://doi.org/10.1145/3607199.3607206},
  researchr = {https://researchr.org/publication/HangLWX23},
  cites = {0},
  citedby = {0},
  pages = {297-314},
  booktitle = {Proceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses, RAID 2023, Hong Kong, China, October 16-18, 2023},
  publisher = {ACM},
}