LATIDIA · Ciberseguridad

s-MDM: Virtualización generativa de variaciones de hardware multidispositivo para DL-SCA portátil

arXiv: 2609.18783v1Tipo de anuncio: nuevo Resumen: el análisis de canales laterales basado en aprendizaje profundo (DL-SCA) sufre con frecuencia una degradación catastrófica del rendimiento en hardware invisible debido al enrutamiento de la placa de circuito impreso

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arXiv:2609.18783v1 Announce Type: new Abstract: Deep Learning-based Side-Channel Analysis (DL-SCA) frequently suffers from catastrophic performance degradation across unseen hardware due to printed circuit board routing differences, silicon process variations, and measurement noise shifts. This poster presents the Synthetic Multiple Device Model (s-MDM), a zero-target-trace generative framework designed to improve cross-device portability. s-MDM combines a structured cVAE generator, a Walsh-Hadamard leakage anchor, continuous style modulation, and decoupled leakage-style--domain critics to synthesize virtual source-device profiles offline. Benchmarked on 32-bit side-channel traces (AES_PTv2), s-MDM maps a precise operational boundary: while physical MDM remains superior on identical electrical clones (D4), s-MDM achieves consistently low key rank on the layout/acquisition-shifted Pinata target, where physical baselines