Detecting Signatures from BPCS-Steganography Using Complexity Histogram Analysis
| Autor: | Hideki Noda, Eiji Kawaguchi, Tomohito Ei, Michiharu Niimi |
|---|---|
| Rok vydání: | 2004 |
| Předmět: |
Steganography
Computer science business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition Signature (logic) Computer Science Applications Image (mathematics) Normal distribution Digital image Computer Science::Computer Vision and Pattern Recognition Histogram Computer Science::Multimedia Media Technology Statistical analysis Artificial intelligence Electrical and Electronic Engineering business Computer Science::Cryptography and Security |
| Zdroj: | The Journal of the Institute of Image Information and Television Engineers. 58:243-250 |
| ISSN: | 1881-6908 1342-6907 |
| DOI: | 10.3169/itej.58.243 |
| Popis: | This paper describes a method for detecting a signature from BPCS-Steganography by attacking it with a statistical analysis of images. BPCS is a technique that hides a large amount of data in digital images. It divides bit-planes produced through bit-plane decomposition from the images into sub-binary images, and embeds noise-like secret data in the sub-images. These sub-images are then extracted by comparing measures known as complexity and threshold values. We consider a complexity histogram representing the relative occurence frequency of the various noisy regions in each bit-plane. The complexity histograms of the sub-images, in which secret data has been embedded, nearly fit a normal distribution for the image containing secret data. Using the correlation coefficients between the complexity histograms, regarded as a BPCS signature, this method distinguishes between natural images and images with secret data embedded. In our experiments, we were able to accurately detecte these signatures using this method. |
| Databáze: | OpenAIRE |
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