A novel encrypted traffic detection model based on detachable convolutional GCN-LSTM

A novel encrypted traffic detection model based on detachable convolutional GCN-LSTM

Abstract With the widespread adoption of network encryption technologies, traditional detection methods increasingly struggle to identify malicious encrypted traffic due to their limited ability to capture structural and behavioral characteristics. To address this issue, this paper proposes a Detach...

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Bibliographic Details
Main Authors: Xiaogang Yuan, Jianxin Wan, Dezhi An, Huan Pei
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Malicious encrypted traffic
Intrusion detection
Detachable convolution
Graph neural network
Attention mechanism
Online Access:https://doi.org/10.1038/s41598-025-13397-2
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