Deep learning for encrypted traffic classification in the face of data drift: An empirical study
Author:
Publisher
Elsevier BV
Subject
Computer Networks and Communications
Reference35 articles.
1. Large-scale mobile app identification using deep learning;Rezaei;IEEE Access,2020
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1. Poster: Understanding and Managing Changes in IoT Device Behaviors for Reliable Network Traffic Inference;Proceedings of the ACM SIGCOMM 2024 Conference: Posters and Demos;2024-08-04
2. Deep learning and pre-training technology for encrypted traffic classification: A comprehensive review;Neurocomputing;2024-08
3. GateKeeper: An UltraLite malicious traffic identification method with dual-aspect optimization strategies on IoT gateways;Computer Networks;2024-08
4. LTI: Encrypted Traffic Classification Framework Considering Data Drift;2024 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom);2024-06-24
5. Comparative analysis of DNS over HTTPS detectors;Computer Networks;2024-06
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