Meshal Alshawi

Cybersecurity Specialization · Cohort 2026

Post-Quantum Secure Federated Intrusion Detection for Military UAV Networks

This project develops a post-quantum secure intrusion detection system for a group of five military UAVs connected to a central control centre. Each UAV trains its intrusion detection model locally using its own network traffic, allowing it to learn patterns of normal and malicious activity without exposing raw data. The UAV then securely sends only the trained model updates to the control centre, where federated learning combines them to improve the global intrusion detection model at control centre. These model updates are protected in transit using post-quantum cryptography, with ML-KEM for secure key establishment, ML-DSA for authentication, and AES-GCM for encrypted and integrity-protected transmission. The main beneficiaries are defence organisations, military UAV operators, and organisations managing security-sensitive autonomous or unmanned systems. The solution can be developed as a cybersecurity software product or managed security service for secure UAV fleet monitoring and collaborative intrusion detection. Its main advantage is the ability to improve cyberattack detection across multiple UAVs while keeping local data private and protecting communication against tampering and future quantum-related security risks.

Read the final report (PDF)