Hiding Data in Images Using Cryptography and Deep Neural Network
This work addresses security challenges in digital forensics and steganography by integrating multiple techniques, though it appears incremental as it builds on prior combinations of these methods.
The paper tackles the problem of secure data hiding in images by combining steganography, cryptography, and deep neural networks to embed one image within another of equal or larger size, resulting in a method that is both secure and non-uniform compared to existing techniques.
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.