Stego-Image Generator (SIG) - Building Steganography Image Database
This provides a needed resource for steganalysis researchers to better evaluate algorithm efficiency, though it is incremental as it builds on existing steganography methods.
The authors tackled the lack of detailed stego-image databases for testing universal steganalysis algorithms by creating a database using various RGB Least Significant Bit steganographic algorithms, which includes specific information like infected rows, modified bits, and affected channels.
Any Universal Steganalysis algorithm developed should be tested with various stego-images to prove its efficiency. This work is aimed to build the stego-image database which is obtained by implementing various RGB Least Significant Bit Steganographic algorithms. Though there are many stego-images sources available on the internet it lacks in the information such as how many rows has been infected by the steganography algorithms, how many bits have been modified and which channel has been affected. These parameters are important for Steganalysis algorithms and it helps to rate its efficiency. Images are chosen from board categories such as animals, nature, person to produce variety of Stego-Image.