Raw quantum measurement statistics are concatenated into feature vectors and authenticated via Mahalanobis nearest-neighbor classification, achieving 100% accuracy on three superconducting processors while enabling drift early warning and adversarial detection.
QPUF 2.0: Exploring quantum physical unclonable functions for security-by-design of energy cyber-physical systems,
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Raw-Curve Quantum Fingerprints: A Mahalanobis Authentication Framework with Drift Early Warning and Adversarial Detection
Raw quantum measurement statistics are concatenated into feature vectors and authenticated via Mahalanobis nearest-neighbor classification, achieving 100% accuracy on three superconducting processors while enabling drift early warning and adversarial detection.