Hiding Data in Images Using Cryptography and Deep Neural Network
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Abstract (arXiv)
Steganography is an art of obscuring data inside another quotidian file of similar or varying types. Hiding data has always been of significant importance to digital forensics. Previously, steganography has been combined with cryptography and neural networks separately. Whereas, this research combines steganography, cryptography with the neural networks all together to hide an image inside another container image of the larger or same size. Although the cryptographic technique used is quite simple, but is effective when convoluted with deep neural nets. Other steganography techniques involve hiding data efficiently, but in a uniform pattern which makes it less secure. This method targets both the challenges and make data hiding secure and non-uniform.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Dec 2019.
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Citing papers per year: 2021: 1; 2022: 3.
4 papers.
- 2022Towards Blind Watermarking: Combining Invertible and Non-invertible Mechanismscited by 61
- 2021Data Hiding with Deep Learning: A Survey Unifying Digital Watermarking and Steganographycited by 23
- 2022EcoFlow: Efficient Convolutional Dataflows for Low-Power Neural Network Acceleratorscited by 1
- 2022Crowdsourced-based Deep Convolutional Networks for Urban Flood Depth Mappingcited by 0
- 2022Towards Blind Watermarking: Combining Invertible and Non-invertible Mechanisms24 Dec 2022
- 2022Crowdsourced-based Deep Convolutional Networks for Urban Flood Depth Mapping6 Sep 2022
- 2022EcoFlow: Efficient Convolutional Dataflows for Low-Power Neural Network Accelerators4 Feb 2022
- 2021Data Hiding with Deep Learning: A Survey Unifying Digital Watermarking and Steganography20 Jul 2021