QUASAR: A Quantum-Classical Neural Network for SAR Satellite Physical-Layer Authentication
X-band SAR satellites (8-12 GHz) play a critical role in disaster response, environmental monitoring, and military intelligence. Yet, they lack robust physical-layer authentication (PLA), a security layer orthogonal to cryptographic solutions. Existing PLA systems, typically based on radio-frequency fingerprinting, are often limited to sub-6 GHz frequencies and rely on classical deep learning. However, this approach underfits the IQ phase nonlinearities that distinguish satellite hardware. In this paper, we present QUASAR, to the best of our knowledge the first quantum-classical hybrid archite
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- LinkedLinked via arxiv author · 85%Vincenzo Sammartino →
“QUASAR: A Quantum-Classical Neural Network for SAR Satellite Physical-Layer Authentication”
- LinkedLinked via arxiv author · 85%Nathanaël Denis →
“QUASAR: A Quantum-Classical Neural Network for SAR Satellite Physical-Layer Authentication”
- LinkedLinked via arxiv author · 85%Roberto Di Pietro →
“QUASAR: A Quantum-Classical Neural Network for SAR Satellite Physical-Layer Authentication”