A novel steganographic algorithm using animations as cover
Information security is gaining widespread importance in distributed decision support systems [T.S. Raghu, and H. Chen, Cyberinfrastructure for homeland security: Advances in information sharing, data mining, and collaboration systems. Decision Support Systems 43 (2007) 13211323]. Conventional steganographic models available in the literature on information hiding use the knowledge of cover-object and stego-object to extract embedded data. Embedding algorithms have been predominantly used in steganography for hiding data whereas encoding algorithms have been used for data compression. This research study proposes a modified model for steganographic system that incorporates encoding algorithms based upon the information theoretic model documented in Cachin [C. Cachin, An Information-Theoretic Model for Steganography, Information and Computation 192 (1) (2004) 4156.]. The differences between the conventional model and the proposed model are analyzed in this study. We further implement the proposed model by designing a novel steganographic algorithm that utilizes animations as cover-objects. The proposed approach is then compared with an encoding algorithm for gif animations and a modified embedding algorithm with animations as the cover. Gifshuffle is a steganographic software that hides data in gif animations. Digital Invisible Ink Toolkit (DIIT) is a software that uses embedding algorithm to conceal data into images. DIIT is remodeled to hide data within animated images in this study. Experiments reveal that the encoding algorithms are suitable for information hiding using animations. The study finds that the proposed encoding framework with animations provides a practical framework for analysis and has a better security performance than Gifshuffle and DIIT. Although the proposed model achieves more hiding rate, Gifshuffle is computationally faster than other techniques.
animation steganographic model information hiding encoding decoding