Western-OC2-Lab/Cross-Layer-Autonomous-Cybersecurity-Framework

This repository includes code for the paper "Towards Zero Touch Networks: Cross-Layer Automated Security Solutions for 6G Wireless Networks" published in IEEE TCOM, focusing on autonomous cybersecurity (physical-layer authentication and cross-layer intrusion detection) using AutoML techniques.

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This framework helps network security engineers develop and deploy robust cybersecurity solutions for 6G wireless networks. It takes raw network traffic data or radio frequency fingerprints and automatically generates optimized machine learning models for detecting intrusions and authenticating devices. This is ideal for network operators and security analysts working with evolving, dynamic network environments.

No commits in the last 6 months.

Use this if you need to build automated security systems for 6G networks that can adapt to changing threats and network conditions without constant manual intervention.

Not ideal if you are working with static, unchanging network environments or do not require advanced automation for cybersecurity model development.

6G network security Intrusion Detection Physical Layer Authentication Network Automation Cybersecurity Operations
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 15 / 25

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14

Forks

5

Language

Jupyter Notebook

License

MIT

Last pushed

Mar 05, 2025

Commits (30d)

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