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  • Intelligent detection of steganography transform based on containers classification

    The possibility of detection of steganography in digital images based on the classification of stegocontainers is investigated. The obtained results demonstrate the effectiveness of using deep neural networks for solving this problem. The LSB method can be detected using EfficientNet b3 architecture. The achieved classification accuracy is above 97%. Using of steganography methods in frequency domain can be effectively detected by classifying their representation in the form of a digital YCrBr model, with augmentation (vertical and horizontal rotations). The classification accuracy is above 77%.

    Keywords: Steganography, stegocontainer, machine learning, classification, digital image, deep learning, CNN, EfficientNet b3, confidentiality, information protection