Securing visible light communications via friendly jamming
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite offering higher security than radio frequency (RF) channels, the broadcast nature of the visible light communication (VLC) channel makes VLC links inherently susceptible to eavesdropping by unauthorized users. In this work, we consider the physical-layer security of VLC links aided by friendly jamming. The jammer has multiple light sources, but does not have access to the data transmitted. The eavesdropper's reception is degraded by a jamming signal that causes no interference to the legitimate receiver. Due to the limited dynamic range of typical light-emitting diodes (LEDs), both the data and jamming signals are subject to amplitude constraints. Therefore, we begin with deriving a closed-form secrecy rate expression for the corresponding wiretap channel, and adopt secrecy rate as the performance measure. Then, we formulate a linear programming problem to maximize the secrecy rate when the eavesdropper's channel is accurately known to the jammer. Finally, we consider robust beamforming to maximize the worst-case secrecy rate when information about the eavesdropper's channel is uncertain due to location uncertainty. The robust scheme makes use of simple linear programming, making real-time implementation feasible in a variety of real-world scenarios.
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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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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