Quantitative steganalysis using binary classifier
In this paper, the problem of determining secret message length using binary steganalytic classifier is researched. It is assumed that a steganalyst is able to cut a large stego image into k smaller images and to apply the binary classification to every one of them. According to the information-theoretic approach to the steganographic security, a steganalyst's expected error calculation formula is derived. Determining the optimal choice of k depended on the properties of a binary classifier and a given image is formulated as a minimization problem. Presented approach can be used to estimate impact of various parameters on stegosystem security against quantitative steganalysis.
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Keywords
количественный стегоанализ, бинарная классификация, quantitative steganalysis, binary classificationAuthors
| Name | Organization | |
| Razinkov E.V. | Razinkov@steganography.ru | |
| Almeev A.N. | azat.almeev@gmail.com |
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