Hide and Speak: Towards Deep Neural Networks for Speech Steganography

@inproceedings{Kreuk2020HideAS,
  title={Hide and Speak: Towards Deep Neural Networks for Speech Steganography},
  author={F. Kreuk and Y. Adi and B. Raj and R. Singh and Joseph Keshet},
  booktitle={INTERSPEECH},
  year={2020}
}
  • F. Kreuk, Y. Adi, +2 authors Joseph Keshet
  • Published in INTERSPEECH 2020
  • Computer Science, Engineering, Mathematics
  • Steganography is the science of hiding a secret message within an ordinary public message, which is referred to as Carrier. Traditionally, digital signal processing techniques, such as least significant bit encoding, were used for hiding messages. In this paper, we explore the use of deep neural networks as steganographic functions for speech data. We showed that steganography models proposed for vision are less suitable for speech, and propose a new model that includes the short-time Fourier… CONTINUE READING
    3 Citations

    Figures, Tables, and Topics from this paper

    Deep Residual Neural Networks for Image in Speech Steganography
    • 1
    • PDF
    Deep Residual Neural Networks for Image in Audio Steganography (Workshop Paper)

    References

    SHOWING 1-10 OF 46 REFERENCES
    Deep Residual Neural Networks for Image in Speech Steganography
    • 1
    • PDF
    Multi-Stage Residual Hiding for Image-Into-Audio Steganography
    • 2
    • PDF
    Hiding Images in Plain Sight: Deep Steganography
    • 103
    • Highly Influential
    • PDF
    Invisible steganography via generative adversarial networks
    • 33
    • PDF
    HiDDeN: Hiding Data With Deep Networks
    • 101
    • Highly Influential
    • PDF
    Deep learning for steganalysis via convolutional neural networks
    • 252
    StegNet: Mega Image Steganography Capacity with Deep Convolutional Network
    • 25
    • PDF
    Using High-Dimensional Image Models to Perform Highly Undetectable Steganography
    • 567
    • PDF
    Embedding a Large Amount of Information Using High Secure Neural Based Steganography Algorithm
    • 30
    • PDF
    Embedding Watermarks into Deep Neural Networks
    • 106
    • PDF