Chaotic Watermarking for Video Authentication in Surveillance Applications
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
Installing video cameras in public facilities for surveillance becomes more and more popular. This paper proposes a novel authentication scheme based on chaotic semi-fragile watermarking. The timing information of video frames is modulated into the parameters of a chaotic system. The system output, which is a noise-like signal, is used as a watermark and embedded into the block-based discrete cosine transform domain. The embedded information is demodulated by a maximum likelihood estimator. Temporal tampering can be detected by the mismatch between the extracted and the observed timing information. In addition, the deviation of the extracted watermark from the original one allows us to locate spatial tampering. It is shown that the proposed scheme can satisfy the peculiar requirements of authenticating a digital video surveillance system.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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