J. Molina-Gil

Hybrid Quantum-Kernel and Quantum-Inspired Machine Learning for TDoS Early Warning in Critical Infrastructure

The proposed framework can improve threat detection and system resilience in critical infrastructure contexts and support the use of kernel-based quantum-inspired representations as a tunable early-warning layer for PSAP traffic monitoring, while also showing that threshold calibration and operational context remain necessary before deployment.