Data hiding in multimedia - theory and applications

Multimedia data hiding or steganography is a means of communication using subliminal channels. The resource for the subliminal communication scheme is the distortion of the original content that can be tolerated. This thesis addresses two main issues of steganographic communication schemes: 1. How does one maximize the distortion introduced without affecting fidelity of the content? 2. How does one efficiently utilize the resource (the distortion introduced) for communicating as many bits of information as possible? In other words, what is a good signaling strategy for the subliminal communication scheme? Close to optimal solutions for both issues are analyzed. Many techniques for the issue for maximizing the resource, viz, the distortion introduced imperceptibly in images and video frames, are proposed. Different signaling strategies for steganographic communication are explored, and a novel signaling technique employing a floating signal constellation is proposed. Algorithms for optimal choices of the parameters of the signaling technique are presented. Other application specific issues like the type of robustness needed are taken into consideration along with the established theoretical background to design optimal data hiding schemes. In particular, two very important applications of data hiding are addressed - data hiding for multimedia content delivery, and data hiding for watermarking (for proving ownership). A robust watermarking protocol for unambiguous resolution of ownership is proposed

Steganalysis of meshes based on 3D wavelet multiresolution analysis

3D steganalysis aims to find the information hidden in 3D models and graphical objects. It is assumed that the information was hidden by 3D steganography or watermarking algorithms. A new set of 3D steganalysis features, derived by using multiresolution 3D wavelet analysis, is proposed in this research study. 3D wavelets relate a given mesh representation with its lower and higher graph resolutions by means of a set of Wavelet Coefficient Vectors (WCVs). The 3D steganalysis features are derived from transformations between a given mesh and its corresponding higher and lower resolutions. They correspond to geometric measures such as ratios and angles between various geometric measures. These features are shown to significantly increase the steganalysis accuracy when detecting watermarks which have been embedded by 3D wavelet-based watermarking algorithms. The proposed features, when used in combination with a previously proposed feature set, is shown to provide the best results in detecting the hidden information embedded by other information hiding algorithms