Future considerations and conclusion
Future work
Due to time and computing limitations, we could not explore all facets of steganography and detectiontechniques. As you saw, we studied the power in our pictures to test for hidden data. Another method which we were unable toexplore was to analyze the noise of the pictures. Adding hidden data adds random noise, so it follows that a properly tuned noisedetection algorithm could recognize whether or not a picture had steganographic data or not.
Conclusion
We explored several steganography techniques and the various detection algorithms associated with them. By usingthe properties of the DCT and our understanding of the frequency domain we developed the zeros hiding method. Zeros hiding proved tobe easier to analyze than bit-o-steg and can hide significantly more data. Unfortunately its ease of detection makes it a lesssecure method. After researching various techniques already implemented, we chose to improve upon one, thus creating ourbit-o-steg method. Bit-o-steg can only hide data in coefficients that were not dropped, thus limiting the amount of data we canhide. However, it greatly enhances the effectiveness of the steganography since it uses a key, making it much more challengingto detect. In the end we found both effective, but the complexity of bit-o-steg makes it more promising. Detection of our methods wascritical to the breadth of our project. By investigating the power in various components of our images we discovered how to detectdata hidden via the zero hiding method. Detecting bit-o-steg required us to draw on past steganography research andstatistically analyze the effects of this type of data hiding. The methods and accompanying detection schemes we developed broadenedour understanding of steganography, which, unlike encryption, allows secret data to be traded hands without raising aneyebrow.