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- W4323922017 abstract "The field of steganography has experienced a surge of interest due to the recent advancements in AI-powered techniques, particularly in the context of multimodal setups that enable the concealment of signals within signals of a different nature. The primary objectives of all steganographic methods are to achieve perceptual transparency, robustness, and large embedding capacity - which often present conflicting goals that classical methods have struggled to reconcile. This paper extends and enhances an existing image-in-audio deep steganography method by focusing on improving its robustness. The proposed enhancements include modifications to the loss function, utilization of the Short-Time Fourier Transform (STFT), introduction of redundancy in the encoding process for error correction, and buffering of additional information in the pixel subconvolution operation. The results demonstrate that our approach outperforms the existing method in terms of robustness and perceptual transparency." @default.
- W4323922017 created "2023-03-12" @default.
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- W4323922017 date "2023-03-08" @default.
- W4323922017 modified "2023-09-26" @default.
- W4323922017 title "Towards Robust Image-in-Audio Deep Steganography" @default.
- W4323922017 doi "https://doi.org/10.48550/arxiv.2303.05007" @default.
- W4323922017 hasPublicationYear "2023" @default.
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