Steganalysis Using Color Model Conversion
This work addresses the need for effective steganalysis techniques to combat cybercrime by detecting concealed information in images, though it appears incremental as it builds on existing color model conversion approaches.
The paper tackled the problem of detecting hidden messages in digital images for forensic purposes by developing a universal steganalysis method using RGB to HSI color model conversion, achieving affirmative results when tested on a custom database of stego-images generated with various LSB steganographic algorithms.
The major threat in cyber crime for digital forensic examiner is to identify, analyze and interpret the concealed information inside digital medium such as image, audio and video. There are strong indications that hiding information inside digital medium has been used for planning criminal activities. In this way, it is important to develop a steganalysis technique which detects the existence of hidden messages inside digital medium. This paper focuses on universal image steganalysis method which uses RGB to HSI colour model conversion. Any Universal Steganalysis algorithm developed should be tested with various stego-images to prove its efficiency. The developed Universal Steganalysis algorithm is tested in stego-image database which is obtained by implementing various RGB Least Significant Bit Steganographic algorithms. Though there are many stego-image 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. Proposed Steganalysis using Colour Model has been tested with our Image Database and the results were affirmative.