The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Revisiting weighted stego-image steganalysis
Abstract
This paper revisits the steganalysis method involving a Weighted Stego-Image (WS) for estimating LSB replacement payload sizes in digital images. It suggests new WS estimators, upgrading the method's three components: cover pixel prediction, least-squares weighting, and bias correction. Wide-ranging experimental results (over two million total attacks) based on images from multiple sources and pre-processing histories show that the new methods produce greatly improved accuracy, to the extent that they outperform even the best of the structural detectors, while avoiding their high complexity. Furthermore, specialised WS estimators can be derived for detection of sequentially-placed payload: they offer levels of accuracy orders of magnitude better than their competitors.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Robust estimation of a location parameter
Huber, P. J. (1964) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177703732 · Cited by 7,228
Cited by
Rich Models for Steganalysis of Digital Images
Fridrich, J., & Kodovsky, J. (2012) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2012.2190402 · Cited by 2,144
Steganalysis by subtractive pixel adjacency matrix
Pevný, T., Bas, P., & Fridrich, J. (2009) · Proceedings of the 11th ACM workshop on Multimedia and security · doi:10.1145/1597817.1597831 · Cited by 769
On detection of median filtering in digital images
Kirchner, M., & Fridrich, J. (2010) · SPIE Proceedings · doi:10.1117/12.839100 · Cited by 278
Random Projections of Residuals for Digital Image Steganalysis
Holub, V., & Fridrich, J. (2013) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2013.2286682 · Cited by 261
Metadata
- Authors
- Ker, A. D., & Böhme, R.
- Venue
- SPIE Proceedings
- Publisher
- SPIE
- Published
- 2008-02-14
- Volume
- 6819
- Pages
- 681905
- ISSN
- 0277-786X (ISSN-L)
- OpenAlex
- W1969171557
- Cited by
- 176
- References
- 1
- FWCI
- 9.08
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Revisiting weighted stego-image steganalysis. https://app.cochat.ai/papers/10.1117/12.766820
- The paper
- Ker, A. D., & Böhme, R. (2008). Revisiting weighted stego-image steganalysis. SPIE Proceedings. https://doi.org/10.1117/12.766820
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
