Towards PHY-Aided Authentication via Weighted Fractional Fourier Transform
Why this work is in the frame
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Bibliographic record
Abstract
Exploiting physical layer (PHY) characteristics has great potential to complement and secure upper-layer authentication protocols. Unlike existing PHY authentication mechanisms requiring special hardware designs, in this paper, we propose a practical PHY- aided authentication approach based on weighted fractional Fourier transform (WFRFT). Instead of exploiting the channel or hardware characteristics that are out of control, the proposed scheme can provide two-fold protection on upper-layer protocols by leveraging the intrinsic PHY features of the transmitted signal. Firstly, WFRFT can hide and forge the modulation paradigm to mislead attackers in signal demodulation. Secondly, WFRFT signal can be adjusted among different patterns automatically and dynamically to provide more security and freedom in PHY authentication, similar to frequency-hopping systems. Numerical simulations and analyses demonstrate that the proposed scheme can achieve more secure authentication with tolerate computational overhead.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it