Reliable Detection of Histogram Shift-Based Steganography Using Payload Invariant Features
Autor: | Hsing Han Liu, Chiang Lung Liu |
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Rok vydání: | 2013 |
Předmět: |
Steganography tools
Steganalysis Steganography business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Scale-invariant feature transform Pattern recognition General Medicine Information hiding Histogram Embedding Computer vision Artificial intelligence Invariant (mathematics) business Mathematics |
Zdroj: | Applied Mechanics and Materials. :3517-3521 |
ISSN: | 1662-7482 |
Popis: | Reversible data hiding techniques can completely recover the cover images after extracting the secret message from the stego images and become a hot research topic recently. The histogram shift-based steganography, which is a kind of reversible data hiding technique, has good performance on imperceptibility. However, it also produces obvious features in the histograms of stego images. In this paper, we propose a steganalysis method based on the payload invariant features to detect the histogram shift-based steganography proposed by Ni et al. In the proposed steganalysis method, the minimum of the sum of the proposed features is first obtained, which is then compared with a predefined threshold to determine an image is a stego or a cover one. Experimental results show that the proposed steganalysis method can provide very high detection accuracy (about 98%) in various payload cases. Compared with the other steganalysis method, the proposed method can provide better detection performance under different embedding ratios and, therefore, is more reliable for detection of the histogram sift-based steganography. |
Databáze: | OpenAIRE |
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