Scalable coding is a technology that encodes a multimedia signal in a scalable manner where various representations can be extracted from a single codestream to fit a wide range of applications. Many new scalable coders such as JPEG 2000 and MPEG-4 FGS offer fine granularity scalability to provide near continuous optimal tradeoff between quality and rates in a large range. This fine granularity scalability poses great new challenges to the design of encryption and authentication systems for scalable media in Digital Rights Management (DRM) and other applications. It may be desirable or even mandatory to maintain a certain level of scalability in the encrypted or signed codestream so that no decryption or re-signing is needed when legitimate adaptations are applied. In other words, the encryption and authentication should be scalable, i.e., adaptation friendly. Otherwise secrets have to be shared with every intermediate stage along the content delivery system which performs adaptation manipulations. Sharing secrets with many parties would jeopardize the overall security of a system since the security depends on the weakest component of the system. In this paper, we first describe general requirements and desirable features for an encryption or authentication system for scalable media, esp. those not encountered with the non-scalable case. Then we present an overview of the current state of the art of technologies in scalable encryption and authentication. These technologies include full and selective encryption schemes that maintain the original or coarser granularity of scalability offered by an unencrypted scalable codestream, layered access control and block level authentication that reduce the fine granularity of scalability to a block level, among others. Finally, we summarize existing challenges and propose future research directions.
The image authentication system SARI proposed by Lin and Chang passes JPEG compression and rejects other malicious manipulations. Some vulnerabilities of the system have been reported recently. In this paper, we propose two new attacks that can compromise the SARI system. The first attack is called a histogram attack which modifies DCT coefficients yet maintains the same relationship between any two DCT coefficients and the same mean values of DCT coefficients. Such a modified image can pass the SARI authentication system. The second attack is an oracle attack which uses an oracle to efficiently find the secret pairs used by SARI in its signature generation. A single image plus an oracle is needed to launch the oracle attack. Fixes to thwart the proposed attacks are also proposed in this paper.
We introduce a scheme for hiding supplementary data into digital video by directly modifying the pixels in the video frames. The techniques requires no separate channel or bit interleaving to transmit the extra information. The data is invisibly embedded using a perception-based projection and quantization algorithm. The data hiding algorithm supports user-defined levels of accessibility and security. We provide several examples of video data hiding including real-time video-in-video and audio-in-video. We also demonstrate the robustness of the data hiding procedure to video degradation and distortions, e.g., those that result from additive noise and compression.
We propose in this paper a novel lossless tree coding algorithm. The technique is a direct extension of the bisection method, the simplest case of the complexity reduction method proposed recently by Kieffer and Yang, that has been used for lossless data string coding. A reduction rule is used to obtain the irreducible representation of a tree, and this irreducible tree is entropy-coded instead of the input tree itself. This reduction is reversible, and the original tree can be fully recovered from its irreducible representation. More specifically, we search for equivalent subtrees from top to bottom. When equivalent subtrees are found, a special symbol is appended to the value of the root node of the first equivalent subtree, and the root node of the second subtree is assigned to the index which points to the first subtree, an all other nodes in the second subtrees are removed. This procedure is repeated until it cannot be reduced further. This yields the irreducible tree or irreducible representation of the original tree. The proposed method can effectively remove the redundancy in an image, and results in more efficient compression. It is proved that when the tree size approaches infinity, the proposed method offers the optimal compression performance. It is generally more efficient in practice than direct coding of the input tree. The proposed method can be directly applied to code wavelet trees in non-iterative wavelet-based image coding schemes. A modified method is also proposed for coding wavelet zerotrees in embedded zerotree wavelet (EZW) image coding. Although its coding efficiency is slightly reduced, the modified version maintains exact control of bit rate and the scalability of the bit stream in EZW coding.
In this paper, we describe an improved version of our previous approach for low bit rate near- perceptually transparent image compression. The method exploits both frequency and spatial domain visual masking effects and uses a combination of Fourier and wavelet representations to encode different bands. The frequency domain masking model is based on the psychophysical masking experimental data of sinusoidal patterns while the spatial domain masking is computed with a modified version of Girod's model. A discrete cosine transform is used in conjunction with frequency domain masking to encode the low frequency subimages. The medium and high frequency subimages are encoded in the wavelet domain with spatial domain masking. The main improvement over our previous technique is that a better model is used to calculate the tolerable error level for the subimages in the wavelet domain, and a boundary control is used to prevent or reduce the ringing noise in the decoded image. This greatly improves the decoded image quality for the same coding bit rates. Experiments show the approach can achieve very high quality to nearly transparent compression at bit rates of 0.2 to 0.4 bits/pixel for the image Lena.