Forensic hash for multimedia information

Digital multimedia such as images and videos are prevalent on today’s internet and cause significant social impact, which can be evidenced by the proliferation of social networking sites with user generated contents. Due to the ease of generating and modifying images and videos, it is critical to establish trustworthiness for online multimedia information. In this paper, we propose a new framework to perform multimedia forensics by using compact side information to reconstruct the processing history of a multimedia document. We refer to this framework as FASHION, standing for Forensic hASH for informatION assurance. As a first step in the modular design for FASHION, we propose new algorithms based on Radon transform and scale space theory to effectively estimate the parameters of geometric transforms and detect local tampering that an image may have undergone. The FASHION framework is designed to answer a much broader range of questions regarding the processing history of multimedia data than simple binary decision from robust image hashing, and also offers more efficient and accurate forensic analysis than multimedia forensic techniques that do not use any side information.