Western-OC2-Lab/AutonomousCyber-AutoML-based-Autonomous-Intrusion-Detection-System

This repository includes code for the paper "Towards Autonomous Cybersecurity: An Intelligent AutoML Framework for Autonomous Intrusion Detection" accepted in AutonomousCyber, ACM CCS, 2024.

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This project offers an automated system to detect cyber intrusions in complex network environments like 5G and future 6G networks. It automatically processes network traffic data, identifies potential threats, and flags suspicious activities without extensive manual oversight. Network security engineers, SOC analysts, and cybersecurity researchers can use this to enhance their defensive capabilities.

No commits in the last 6 months.

Use this if you need to build or improve an intrusion detection system for next-generation networks and want to automate the entire process from data handling to model deployment.

Not ideal if you are looking for a simple, off-the-shelf security appliance or do not have the technical expertise to integrate and manage machine learning workflows.

network-security intrusion-detection cybersecurity-automation threat-detection 5G-security
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 12 / 25

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34

Forks

5

Language

Jupyter Notebook

License

MIT

Last pushed

Nov 08, 2024

Commits (30d)

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