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PART III: SECURITY, PRIVACY AND INFORMATION ASSURANCE

  My research on multimedia security consists of three parts, multimedia authentication, copyright protection and theoretical information hiding capacity.

Multimedia authentication techniques are required in order to ensure trustworthiness of multimedia data. Its objective is to detect or prevent integrity tampering on video content in either the syntactic level or semantic level. We proposed a robust digital signature technique that can unambiguously distinguish some content-preserving manipulations from malicious tampering. We proposed a unique Self-Authentication-and-Recovery Image (SARI) system, which results in producing smart images that can help to detect the changed location and recovery from the manipulations.

  Watermarking is a promising solution that can protect the copyright of multimedia data through transcoding. A reasonable expectation of applying watermarking techniques for copyright protection is to consider specific application scenarios, because the distortion behavior involved in these cases (geometric distortion and pixel value distortion) could be reasonably predictable. We proposed a practical public watermarking algorithm that is robust to rotation, scaling, and/or translation (RST) distortion. It plays an important role in our design of the first watermarking technique, which survives the image print-and-scan process.

   In addition, we examined an important issue regarding the maximum amount of watermark information without causing noticeable perceptual degradation.  This is an original work in analyzing the theoretical watermarking capacity bounds for digital images, based on the information theory and the characteristics of the human vision system.    

Robust Digital Signature and Self-Authentication-and-Recovery Image (SARI) System

 The well-known adage that “seeing is believing” is no longer true due to the pervasive and powerful multimedia manipulation tools. Such development has decreased the credibility that multimedia data such as photos, video or audio clips, printed documents, etc. used to command.

 We first proposed a robust digital signature technique which substitute the hash function in the digital signature with a content-preserving robust visual hash. We studied the methodologies behind multimedia compression techniques and then developed several theories that guided the design of visual hash based on unambiguous invariant signal properties of multimedia data across various compressions.  Because of the adequateness of the theories in both the theoretical domain and practical system implementation domain, the proposed system has been proved to be successful in achieving error-free capabilities in distinguishing content-preserving standard compressions from malicious compressions.

 We then proposed a unique Self-Authentication-and-Recovery Image (SARI) system. SARI utilizes a novel semi-fragile watermarking technique that accepts JPEG lossy compression on the watermarked image to a pre-determined quality factor, and rejects malicious attacks. The authenticator can identify the positions of corrupted blocks, and recover them with approximations of the original ones. In addition to JPEG compression, adjustments of the brightness of the image within reasonable ranges are also acceptable using the proposed authenticator. The security of the proposed method is achieved by using the secret block mapping function which controls the signature generating/ embedding processes.

Here is an example:

(Collaborators: Shih-Fu Chang) 

Robust Watermarks Surviving Rotation, Scaling, Cropping, and Image Print-and-Scan Process

 Watermarking has been considered to be a promising solution that can protect the copyright of multimedia data through transcoding, because the embedded message is always included in the data. We first proposed a public watermark technique that is invariant to geometric distortions. Our method does not embed an additional registration pattern or embed watermark in a recognizable structure, so there is no need to identify and invert them. In particular, we are concerned with distortions due to rotation, scale and/or translation (RST).

 We then proposed a hypothetical model of the pixel value distortions. To our knowledge, in 1999, there was no existing appropriate model in the literature to describe the pixel value distortions in PS process. Therefore, we propose a  hypothetical model based on our experiments and some relative literature. Although more experiments are needed to verify its validity, we found this model is appropriate in our experiments using different printers and scanners, as it shows several characteristics of rescanned images. We also note that, in general image editing processes, geometric distortion cannot be adequately modeled by the well-known rotation, scaling, and translation (RST) effects, because of the effect of cropping. In the PS process, the scanned image may cover part of the original picture and/or part of the background, and may have an arbitrarily cropped size. These changes, especially that of image size, will introduce significant changes of the DFT coefficients. Thus, we analyzed the geometric distortion in the PS process, and then focus on the changes of DFT coefficients for invariants extraction. Based on these adjustments, we then applied our proposed technique for watermarking design on the protection of copyright information through image print-and-scan process.

 (Collaborators: Jeffrey Bloom, Min Wu, Ingemar Cox, Matthew Miller, Yuiman Rui, Shih-Fu Chang) 

Theoretical Data Hiding Capacity Bound for Digital Images

 In addition, we study the theoretic issue with regard to watermarking embedding space existing in multimedia data. This space should depend on the properties of human audio-visual system. It is a complex scientific question that we may not be able to find a thorough answer in this thesis. Our objective is to study existing human vision system models, achieve better understanding of various watermarking space, and then develop information-theoretic estimation of information capacity via watermark. We investigate watermarking capacity in three directions: the zero-error capacity for public watermarking in magnitude-bounded noisy environments, the watermarking capacity based on domain-specific masking effects, and the watermarking capacity issues based on sophisticated Human Vision System models.

 First, we investigated the watermarking capacity based on content-independent constraints on the magnitudes of watermarks and noises. We showed that, in the case that the noise magnitudes are constrained, a capacity bound with “deterministic” zero error can be actually achieved. We showed that, in an environment with finite states and bounded noises, transmission error can be actually zero, instead of approaching zero as contemplated in Shannon's channel capacity theory. Specifically, we found the zero-error capacity for private and public watermarking in a magnitude-bounded noisy environment. An example case is that, assuming the added noise is due to quantization (as in JPEG), we can calculate the zero-error capacity based on the setting of the magnitude constraints on watermark and noise. Note that we consider all pixels, watermarks and noises are discrete values, which occur in realistic cases. Second, we found out the watermarking capacity based on domain-specific masking effects. We showed the capacity of private watermarking in which the power constraints are not uniform. Then, we applied several domain-specific HVS approximation models to estimate the power constraints and then show the theoretical watermarking capacity of an image in a general noisy environment. Third, we conducted the watermarking capacity issues based on actual Human Vision System models. We described in details the most sophisticated Human Vision Systems developed by Daly and Lubin. Then, we discuss issues and possible directions in applying these models to estimation of the watermarking capacity.

 (Collaborators: Shih-Fu Chang) 

Last Updated: 01/24/2006