Tfe-gnn: A temporal fusion encoder using graph neural networks for fine-grained encrypted traffic classification
Encrypted traffic classification is receiving widespread attention from researchers and
industrial companies. However, the existing methods only extract flow-level features, failing …
industrial companies. However, the existing methods only extract flow-level features, failing …
A new platform for machine-learning-based network traffic classification
This study provides a new platform for classifying encrypted network traffic based on
machine learning (ML) techniques. The architecture of the platform is designed for real …
machine learning (ML) techniques. The architecture of the platform is designed for real …
Interaction matters: Encrypted traffic classification via status-based interactive behavior graph
Y Li, X Chen, W Tang, Y Zhu, Z Han, Y Yue - Applied Soft Computing, 2024 - Elsevier
Accurately classifying encrypted traffic is the indispensable cornerstone for network
management and Quality of Service (QoS) improvement. Although existing works that learn …
management and Quality of Service (QoS) improvement. Although existing works that learn …
BehavSniffer: Sniff User Behaviors from the Encrypted Traffic by Traffic Burst Graphs
With the increasing popularity of encryption pro-tocols in application and the rapid
development of network applications, traffic classification has become a major challenge for …
development of network applications, traffic classification has become a major challenge for …
[HTML][HTML] An Encrypted Traffic Classification Approach Based on Path Signature Features and LSTM
Y Mei, N Luktarhan, G Zhao, X Yang - Electronics, 2024 - mdpi.com
Classifying encrypted traffic is a crucial aspect of network security. However, popular
methods face several limitations, such as a reliance on feature engineering and the need for …
methods face several limitations, such as a reliance on feature engineering and the need for …
Detection and utilization of new-type encrypted network traffic in distributed scenarios
P Zhang, F Chen, H Yue - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
Abstract Encrypted Network Traffic Classification (ENTC) is a crucial task in network
management. The existing ENTC schemes usually imply two hypotheses. First, adopting a …
management. The existing ENTC schemes usually imply two hypotheses. First, adopting a …
Improved temporal IoT device identification using robust statistical features
Abstract The Internet of Things (IoT) is becoming more prevalent in our daily lives. A recent
industry report projected the global IoT market to be worth more than USD 4 trillion by 2032 …
industry report projected the global IoT market to be worth more than USD 4 trillion by 2032 …
One Train for Two Tasks: An Encrypted Traffic Classification Framework Using Supervised Contrastive Learning
As network security receives widespread attention, encrypted traffic classification has
become the current research focus. However, existing methods conduct traffic classification …
become the current research focus. However, existing methods conduct traffic classification …
A robust supervised machine learning based approach for offline-online traffic classification of software-defined networking
Due to the exponential increase of internet applications and network users, network traffic
classification (NTC) is a crucial study subject. It successfully improves network service …
classification (NTC) is a crucial study subject. It successfully improves network service …
Granular network traffic classification for streaming traffic using incremental learning and classifier Chain
In modern networks, network visibility is of utmost importance to network operators.
Accordingly, granular network traffic classification quickly rises as an essential technology …
Accordingly, granular network traffic classification quickly rises as an essential technology …