An Uncertainty-Based Traffic Training Approach to Efficiently Identifying Encrypted Proxies-Reference-Cited by-同舟云学术

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An Uncertainty-Based Traffic Training Approach to Efficiently Identifying Encrypted Proxies

Published:2020-11-23 Issue: Volume: Page:
ISSN:
Container-title:2020 12th International Conference on Advanced Infocomm Technology (ICAIT)
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Author:

Zhang Xianlei,Ma Xiaobo,Han Xiao,She Bo,Li Wei

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9315292/9315373/09315573.pdf?arnumber=9315573

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Packet Bytes-Based Abnormal Encrypted Proxy Traffic Identification;2024 IEEE 30th International Conference on Telecommunications (ICT);2024-06-24

2. Growth-Adaptive Distillation Compressed Fusion Model for Network Traffic Identification Based on Iot Cloud-Edge Collaboration;2024

3. Recognition of Abnormal Proxy Voice Traffic in 5G Environment Based on Deep Learning^*;2022 18th International Conference on Mobility, Sensing and Networking (MSN);2022-12

4. On the Performance of Deep Learning Methods for Identifying Abnormal Encrypted Proxy Traffic;2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom);2022-12

5. Detecting ShadowsocksR User Based on Intelligence of Cyber Entities;Security and Communication Networks;2022-08-24

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