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FreqSpaNet: Frequency and Spatial Learning of SFPF for Physical Layer Hardware Integrity Detection

Paper recorded by Signals 4 on 2026-09-15 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-15 on arXiv · recorded by Signals 4 on 2026-09-16

Category: cs.LG · 机器学习 · first seen 2026-09-16

Abstract

Unauthorized hardware replacement can preserve a wireless device's logical identity while altering its physical implementation, posing a challenge to hardware integrity verification. Spatio-frequency polarization fingerprints (SFPFs) capture device-dependent responses across multiple frequencies and directions, but their frequency and spatial dimensions exhibit different structural dependencies. W

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#27 most recent of 215 cs.LG papers we have recorded · ↑ newer: Interpretable Multi-Instance Learning Enables Early Prediction of Key · ↓ older: Bridging the Gap Between Homogeneous and Heterogeneous Asynchronous Op
Cite this page: FreqSpaNet: Frequency and Spatial Learning of SFPF for Physical Layer Hardware Integrity Detection: the #27 most recent of 215 cs.LG papers we have recorded (as of 2026-09-15). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/freqspanet-frequency-and-spatial-learning-of-sfpf-for-physical-layer-hardware-in.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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