Industrial Control Malicious Traffic Anomaly Detection System Based on Deep Autoencoder

Weiping Wang, Weiping Wang, Weiping Wang, Weiping Wang, Chunyang Wang, Chunyang Wang, Chunyang Wang, Chunyang Wang, Yongzhen Guo, Yongzhen Guo, Manman Yuan, Manman Yuan, Manman Yuan, Manman Yuan, Xiong Luo, Xiong Luo, Xiong Luo, Xiong Luo, Yang Gao

Open source

DOI: 10.3389/fenrg.2020.555145
Published: 1
Container: Frontiers in Energy Research
Publisher: Not recorded
Open access: yes

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uncertain Score 53/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

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Cite this work

BibTeX

@article{allodium:10.3389/fenrg.2020.555145,
  title = {Industrial Control Malicious Traffic Anomaly Detection System Based on Deep Autoencoder},
  author = {Weiping Wang and Weiping Wang and Weiping Wang and Weiping Wang and Chunyang Wang and Chunyang Wang and Chunyang Wang and Chunyang Wang and Yongzhen Guo and Yongzhen Guo and Manman Yuan and Manman Yuan and Manman Yuan and Manman Yuan and Xiong Luo and Xiong Luo and Xiong Luo and Xiong Luo and Yang Gao},
  year = {2021},
  journal = {Frontiers in Energy Research},
  doi = {10.3389/fenrg.2020.555145},
  url = {https://doi.org/10.3389/fenrg.2020.555145}
}

RIS

TY  - JOUR
TI  - Industrial Control Malicious Traffic Anomaly Detection System Based on Deep Autoencoder
AU  - Weiping Wang
AU  - Weiping Wang
AU  - Weiping Wang
AU  - Weiping Wang
AU  - Chunyang Wang
AU  - Chunyang Wang
AU  - Chunyang Wang
AU  - Chunyang Wang
AU  - Yongzhen Guo
AU  - Yongzhen Guo
AU  - Manman Yuan
AU  - Manman Yuan
AU  - Manman Yuan
AU  - Manman Yuan
AU  - Xiong Luo
AU  - Xiong Luo
AU  - Xiong Luo
AU  - Xiong Luo
AU  - Yang Gao
PY  - 2021
JO  - Frontiers in Energy Research
DO  - 10.3389/fenrg.2020.555145
UR  - https://doi.org/10.3389/fenrg.2020.555145
ER  -

APA

Wang, W., Wang, W., Wang, W., Wang, W., Wang, C., Wang, C., Wang, C., Wang, C., Guo, Y., Guo, Y., Yuan, M., Yuan, M., Yuan, M., Yuan, M., Luo, X., Luo, X., Luo, X., Luo, X., & Gao, Y. (2021). Industrial Control Malicious Traffic Anomaly Detection System Based on Deep Autoencoder. Frontiers in Energy Research. https://doi.org/10.3389/fenrg.2020.555145

Source records

doaj · retrieved 2026-09-25T06:25:10.722Z