Dynamic multi-scale topological representation for enhancing network intrusion detection

M Zhong, M Lin, Z He - Computers & Security, 2023 - Elsevier
Network intrusion detection systems (NIDS) play a crucial role in maintaining network
security. However, current NIDS techniques tend to neglect the topological structures of …

A Survey on Graph Neural Networks for Intrusion Detection Systems: Methods, Trends and Challenges

M Zhong, M Lin, C Zhang, Z Xu - Computers & Security, 2024 - Elsevier
Intrusion detection systems (IDS) play a crucial role in maintaining network security. With the
increasing sophistication of cyber attack methods, traditional detection approaches are …

Flow topology-based graph convolutional network for intrusion detection in label-limited IoT networks

X Deng, J Zhu, X Pei, L Zhang, Z Ling… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Given the distributed nature of the massively connected “Things” in IoT, IoT networks have
been a primary target for cyberattacks. Although machine learning based network intrusion …

Learning to classify: A flow-based relation network for encrypted traffic classification

W Zheng, C Gou, L Yan, S Mo - Proceedings of The Web Conference …, 2020 - dl.acm.org
As the size and source of network traffic increase, so does the challenge of monitoring and
analyzing network traffic. The challenging problems of classifying encrypted traffic are the …

Graph mining for cybersecurity: A survey

B Yan, C Yang, C Shi, Y Fang, Q Li, Y Ye… - ACM Transactions on …, 2023 - dl.acm.org
The explosive growth of cyber attacks today, such as malware, spam, and intrusions, has
caused severe consequences on society. Securing cyberspace has become a great concern …

An encrypted traffic classification method combining graph convolutional network and autoencoder

B Sun, W Yang, M Yan, D Wu, Y Zhu… - 2020 IEEE 39th …, 2020 - ieeexplore.ieee.org
The increase in the source and size of encrypted network traffic brings significant challenges
for network traffic analysis. The challenging problem in the encrypted traffic classification …

GCN‐ETA: High‐Efficiency Encrypted Malicious Traffic Detection

J Zheng, Z Zeng, T Feng - Security and Communication …, 2022 - Wiley Online Library
Encrypted network traffic is the principal foundation of secure network communication, and it
can help ensure the privacy and integrity of confidential information. However, it hides the …

USAGE: Uncertain flow graph and spatio-temporal graph convolutional network-based saturation attack detection method

K Wang, Y Cui, Q Qian, Y Chen, C Guo… - Journal of Network and …, 2023 - Elsevier
With the development of Software-Defined Networking (SDN), its security problems have
attached interests from academia. The saturation attack targeted at the SDN switch is one of …

Pedestrian flow prediction in open public places using graph convolutional network

M Liu, L Li, Q Li, Y Bai, C Hu - ISPRS International Journal of Geo …, 2021 - mdpi.com
Open public places, such as pedestrian streets, parks, and squares, are vulnerable when
the pedestrians thronged into the sidewalks. The crowd count changes dynamically over …

GAP-WF: Graph attention pooling network for fine-grained SSL/TLS Website fingerprinting

J Lu, G Gou, M Su, D Song, C Liu… - … Joint Conference on …, 2021 - ieeexplore.ieee.org
As an important part of network management, website fingerprinting has become one of the
hottest topics in the field of encrypted traffic classification. Website fingerprinting aims to …