On steganalysis of random LSB embedding in continuous-tone images
Why this work is in the frame
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Bibliographic record
Abstract
We present an LSB steganalysis technique that can detect the existence of hidden messages that are randomly embedded in the least significant bits of natural continuous-tone images. The technique is inspired by the recent work of J. Fridrich et al. (see Proc. ACM Workshop on Multimedia and Security, p.27-30, 2001) and just like their work, it can also precisely measure the length of the embedded message, even when the hidden message is very short relative to the image size. The key to our success is the formation of some subsets of pixels whose cardinalities change with LSB embedding, and such changes can be precisely quantified under the assumption that the embedded bits are randomly scattered. Interestingly, our study on steganalysis of LSB embedding sheds light on the work of Fridrich et al. on the detection of LSB embedding, and offers an analytical proof of an observation made by them.
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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 | 0.001 | 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 | 0.002 |
| 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