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RollingEvidence: Autoregressive Video Evidence via Rolling Shutter Effect

Talkat USENIX Security '25 · 2025-08-13..08-15· [security, computer-vision]
name:Feng Qian
linkedin:fqian
links:none on file
name:Tao Luo
links:none on file
name:Shiqi Xu
links:none on file
name:Zhijun Yu
links:none on file
name:Wei Wang
linkedin:weiww
slides:none on file

An active system embeds rolling shutter stripes by modulating an LED with a 16‑FSK LED probe and records them on commodity CMOS phones; an autoregressive encoder produces 4,096‑dim autoregressive tokens tied to device cryptographic keys and prior frames, packed into overlapping windows (optimal 30–150 frames). A multitask deep network extracts stripe intensity curves, decodes probes, and flags tampered frames with a 98% quantile test and exponential‑min implication; prototype (smartphone + Arduino Uno) shows zero FAR above −18.19 dB SNR and ≈99.5% detection accuracy.

AI-written summary · about

  1. 0:00RollingEvidence system
  2. 1:15Rolling shutter probes
  3. 3:03Calibrating strip patterns
  4. 4:27Stochastic probe encoding
  5. 6:13Security against tampering
  6. 7:18Prototype validation
  7. 9:50Key contributions
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