GCN-MHSA: A novel malicious traffic detection method based on graph convolutional neural network and multi-head self-attention mechanism - researchr publication related

researchr

You are not signed in
Sign in
Sign up

Jinfu Chen 0001, Haodi Xie, Saihua Cai, Luo Song, Bo Geng, Wuhao Guo. GCN-MHSA: A novel malicious traffic detection method based on graph convolutional neural network and multi-head self-attention mechanism. Computers & Security, 147:104083, 2024. [doi]

The following publications are possibly variants of this publication:

A malicious network traffic detection model based on bidirectional temporal convolutional network with multi-head self-attention mechanismSaihua Cai, Han Xu, Mingjie Liu, Zhilin Chen, Guofeng Zhang 0015. compsec, 136:103580, January 2024. [doi]

TLS-MHSA: An Efficient Detection Model for Encrypted Malicious Traffic based on Multi-Head Self-Attention MechanismJinfu Chen 0001, Luo Song, Saihua Cai, Haodi Xie, Shang Yin, Bilal Ahmad. tissec, 26(4), November 2023. [doi]

Malicious Controller Detection Mechanism based on Graph Convolutional Neural NetworkYongan Guo, Hao Huang, Hao She, Yuao Wang. wcsp 2023: 773-778 [doi]

A novel intelligent fault diagnosis method of bearing based on multi-head self-attention convolutional neural networkHang Ren, Shaogang Liu, Bo Qiu, Hong Guo, Dan Zhao. aiedam, 38, 2024. [doi]

Malicious Code Detection under 5G HetNets Based on a Multi-Objective RBM ModelZhihua Cui, Yaru Zhao, Yang Cao, Xingjuan Cai, Wensheng Zhang, Jinjun Chen. network, 35(2):82-87, 2021. [doi]

runs on WebDSL