Cover Image

EG-ConMix: An Intrusion Detection Method based on Graph Contrastive Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wu, Lijin, Lei, Shanshan, Liao, Feilong, Zheng, Yuanjun, Liu, Yuxin, Fu, Wentao, Song, Hao, Zhou, Jiajun
Format:	Preprint
Published:	2024
Subjects:	Cryptography and Security Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Multi-view Correlation-aware Network Traffic Detection on Flow Hypergraph
by: Zhou, Jiajun, et al.
Published: (2025)

Entente: Cross-silo Intrusion Detection on Network Log Graphs with Federated Learning
by: Xu, Jiacen, et al.
Published: (2025)

AOC-IDS: Autonomous Online Framework with Contrastive Learning for Intrusion Detection
by: Zhang, Xinchen, et al.
Published: (2024)

Understanding AI Methods for Intrusion Detection and Cryptographic Leakage
by: Zilouchian, Reza, et al.
Published: (2026)

An Investigation into the Performance of Non-Contrastive Self-Supervised Learning Methods for Network Intrusion Detection
by: Fard, Hamed, et al.
Published: (2025)

No Data? No Problem: Synthesizing Security Graphs for Better Intrusion Detection
by: Huang, Yi, et al.
Published: (2025)

SoK: Harmonizing Attack Graphs and Intrusion Detection Systems
by: Agiollo, Andrea, et al.
Published: (2026)

VAEMax: Open-Set Intrusion Detection based on OpenMax and Variational Autoencoder
by: Qiu, Zhiyin, et al.
Published: (2024)

A Contrastive Federated Semi-Supervised Learning Intrusion Detection Framework for Internet of Robotic Things
by: Zeng, Yifan
Published: (2025)

Towards Stealthy and Effective Backdoor Attacks on Lane Detection: A Naturalistic Data Poisoning Approach
by: Liao, Yifan, et al.
Published: (2025)

GRIDAI: Generating and Repairing Intrusion Detection Rules via Collaboration among Multiple LLM-based Agents
by: Li, Jiarui, et al.
Published: (2025)

Self-Supervised Transformer-based Contrastive Learning for Intrusion Detection Systems
by: Koukoulis, Ippokratis, et al.
Published: (2025)

MirGuard: Towards a Robust Provenance-based Intrusion Detection System Against Graph Manipulation Attacks
by: Sang, Anyuan, et al.
Published: (2025)

From Alerts to Intelligence: A Novel LLM-Aided Framework for Host-based Intrusion Detection
by: Sun, Danyu, et al.
Published: (2025)

Are We There Yet? Unraveling the State-of-the-Art Graph Network Intrusion Detection Systems
by: Wang, Chenglong, et al.
Published: (2025)

GraphFaaS: Serverless GNN Inference for Burst-Resilient, Real-Time Intrusion Detection
by: Wang, Lingzhi, et al.
Published: (2025)

AegisMCP: Online Graph Intrusion Detection for Tool-Augmented LLMs on Edge Devices
by: Zhan, Zhonghao, et al.
Published: (2025)

Vehicular Intrusion Detection System for Controller Area Network: A Comprehensive Survey and Evaluation
by: Liu, Yangyang, et al.
Published: (2025)

Simplicity over Complexity: An ARN-Based Intrusion Detection Method for Industrial Control Network
by: Liu, Ziyi, et al.
Published: (2024)

On the Challenges of Holistic Intrusion Detection in ICS
by: Lenz, Stefan, et al.
Published: (2026)

ConCap: Practical Network Traffic Generation for (ML- and) Flow-based Intrusion Detection Systems
by: Verkerken, Miel, et al.
Published: (2025)

A Novel Byte-Level Flow-to-Image Encoding Method for Network Intrusion Detection Systems
by: Mu, Ziyu, et al.
Published: (2026)

METANOIA: A Lifelong Intrusion Detection and Investigation System for Mitigating Concept Drift
by: Ying, Jie, et al.
Published: (2024)

Self-Supervised Learning of Graph Representations for Network Intrusion Detection
by: Guerra, Lorenzo, et al.
Published: (2025)

Deployment Challenges of Industrial Intrusion Detection Systems
by: Wolsing, Konrad, et al.
Published: (2024)

REAL-IoT: Characterizing GNN Intrusion Detection Robustness under Practical Adversarial Attack
by: Zhan, Zhonghao, et al.
Published: (2025)

xIDS-EnsembleGuard: An Explainable Ensemble Learning-based Intrusion Detection System
by: Adil, Muhammad, et al.
Published: (2025)

ACORN-IDS: Adaptive Continual Novelty Detection for Intrusion Detection Systems
by: Fuhrman, Sean, et al.
Published: (2026)

CITADEL: Continual Anomaly Detection for Enhanced Learning in IoT Intrusion Detection
by: Li, Elvin, et al.
Published: (2025)

Quantization-aware Neural Architectural Search for Intrusion Detection
by: Acharya, Rabin Yu, et al.
Published: (2023)

Phishing Detection in Ethereum via Temporal Graph Contrastive Learning
by: Wu, Cong, et al.
Published: (2026)

Evaluating MCC for Low-Frequency Cyberattack Detection in Imbalanced Intrusion Detection Data
by: Thiyagarajan, Prameshwar, et al.
Published: (2025)

LIGHT-HIDS: A Lightweight and Effective Machine Learning-Based Framework for Robust Host Intrusion Detection
by: Gungor, Onat, et al.
Published: (2025)

A PUF-Based Security Framework for Fault and Intrusion Detection
by: Oun, Ahmed, et al.
Published: (2026)

Deep Reinforcement Learning for Intrusion Detection in IoT: A Survey
by: Gueriani, Afrah, et al.
Published: (2024)

QML-IDS: Quantum Machine Learning Intrusion Detection System
by: Abreu, Diego, et al.
Published: (2024)

Assessing Generalisation Capability of Machine Learning Models for Intrusion Detection
by: Hossain, Md Zakir, et al.
Published: (2026)

The Role of Learning in Attacking ML-based Network Intrusion Detection
by: Domico, Kyle, et al.
Published: (2026)

Intrusion Detection System Using Deep Learning for Network Security
by: Chatterjee, Soham, et al.
Published: (2025)

Federated Intrusion Detection System Based on Unsupervised Machine Learning
by: Gourceyraud, Maxime, et al.
Published: (2025)