The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

[서평]「Applied Cryptography」

Throughout this article, we concentrate on the transcoding of block-based video coding schemes that use hybrid discrete cosine transform (DCT) and motion compensation (MC). In such schemes, the frames of the video sequence are divided into macroblocks (MBs), where each MB typically consists of a luminance block (e.g., of size 16 /spl times/ 16, or alternatively, four 8 /spl times/ 8 blocks) along with corresponding chrominance blocks (e.g., 8 /spl times/ 8 Cb and 8 /spl times/ 8 Cr). This article emphasizes the processing that is done on the luminance components of the video. In general, the chrominance components can be handled similarly and will not be discussed in this article. We first provide an overview of the techniques used for bit-rate reduction and the corresponding architectures that have been proposed. Then, we describe the advances regarding spatial and temporal resolution reduction techniques and architectures. Additionally, an overview of error resilient transcoding is also provided, as well as a discussion of scalable coding techniques and how they relate to video transcoding. Finally, the article ends with concluding remarks, including pointers to other works on video transcoding that have not been covered in this article, as well as some future directions.

Video transcoding architectures and techniques: an overview

Image quality assessment (IQA) has been a topic of intense research over the last several decades. With each year comes an increasing number of new IQA algorithms, extensions of existing IQA algorithms, and applications of IQA to other disciplines. In this article, I first provide an up-to-date review of research in IQA, and then I highlight several open challenges in this field. The first half of this article provides discuss key properties of visual perception, image quality databases, existing full-reference, no-reference, and reduced-reference IQA algorithms. Yet, despite the remarkable progress that has been made in IQA, many fundamental challenges remain largely unsolved. The second half of this article highlights some of these challenges. I specifically discuss challenges related to lack of complete perceptual models for: natural images, compound and suprathreshold distortions, and multiple distortions, and the interactive effects of these distortions on the images. I also discuss challenges related to IQA of images containing nontraditional, and I discuss challenges related to the computational efficiency. The goal of this article is not only to help practitioners and researchers
keep abreast of the recent advances in IQA, but to also raise awareness of the key limitations of current IQA knowledge.

/pdf/seven-challenges-in-image-quality-assessment-past-present-4y53obboox.pdf

Seven Challenges in Image Quality Assessment: Past, Present, and Future Research

Video transcoding, due to its high practical values for a wide range of networked video applications, has become an active research topic. We outline the technical issues and research results related to video transcoding. We also discuss techniques for reducing the complexity, and techniques for improving the video quality, by exploiting the information extracted from the input video bit stream.

/pdf/digital-video-transcoding-4etxunv3ur.pdf

Digital Video Transcoding

One of the fundamental challenges in deploying multimedia systems, such as telemedicine, education, space endeavors, marketing, crisis management, transportation, and military, is to deliver smooth and uninterruptible flow of audio-visual information, anytime and anywhere. A multimedia system may consist of various devices (PCs, laptops, PDAs, smart phones, etc.) interconnected via heterogeneous wireline and wireless networks. In such systems, multimedia content originally authored and compressed with a certain format may need bit rate adjustment and format conversion in order to allow access by receiving devices with diverse capabilities (display, memory, processing, decoder). Thus, a transcoding mechanism is required to make the content adaptive to the capabilities of diverse networks and client devices. A video transcoder can perform several additional functions. For example, if the bandwidth required for a particular video is fluctuating due to congestion or other causes, a transcoder can provide fine and dynamic adjustments in the bit rate of the video bitstream in the compressed domain without imposing additional functional requirements in the decoder. In addition, a video transcoder can change the coding parameters of the compressed video, adjust spatial and temporal resolution, and modify the video content and/or the coding standard used. This paper provides an overview of several video transcoding techniques and some of the related research issues. We introduce some of the basic concepts of video transcoding, and then review and contrast various approaches while highlighting critical research issues. We propose solutions to some of these research issues, and identify possible research directions.

/pdf/video-transcoding-an-overview-of-various-techniques-and-575ua9xyn2.pdf

Video transcoding: an overview of various techniques and research issues

Image authentication is important in content delivery via untrusted intermediaries, such as peer-to-peer (P2P) file sharing. Many differently encoded versions of the original image might exist. On the other hand, intermediaries might tamper with the contents. Distinguishing the legitimate diversity of encodings from malicious manipulation is the challenge addressed in this paper. We develop a novel approach based on distributed source coding for the problem of backward-compatible image authentication. The key idea is to provide a Slepian-Wolf encoded quantized image projection as authentication data. This version can be correctly decoded only with the help of an authentic image as side information. Distributed source coding provides the desired robustness against legitimate encoding variations, while detecting illegitimate modification. We demonstrate false acceptance rates close to zero for authentication data sizes that are only a few percent of the compressed image size.

/pdf/image-authentication-based-on-distributed-source-coding-17pv87efv5.pdf

Image Authentication Based on Distributed Source Coding

This paper presents a reduced-reference image quality assessment scheme using distributed source coding for remotely monitoring image quality. In our scheme, an image server extracts a feature vector from the original image and transmits its Slepian-Wolf syndrome using an LDPC encoder. With the rate of the Slepian-Wolf bitstream chosen according to a predetermined admissible image quality, the receiver can reconstruct the feature vector using its received image, as side information, as long as the quality is higher than the admissible quality. Thus the receiver can determine the received image quality using the reconstructed feature vector. Simulation results show that distributed source coding can reduce the bit-rate of the feature vector by 50% and achieve better compression performance than conventional source coding.

Reduced-reference image quality assessment using distributed source coding

We present a novel approach using distributed source coding for image authentication. The key idea is to provide a Slepian-Wolf encoded quantized image projection as authentication data. This version can be correctly decoded with the help of an authentic image as side information. Distributed source coding provides the desired robustness against legitimate variations while detecting illegitimate modification. The decoder incorporating expectation maximization algorithms can authenticate images which have undergone contrast, brightness, and affine warping adjustments. Our authentication system also offers tampering localization by using the sum-product algorithm.

Image Authentication Using Distributed Source Coding

A method transcodes a compressed multi-layer video bitstream that includes a base layer bitstream and an enhancement layer bitstream. The base and enhancement layers are first partially decoded, and then the partially decoded signals are combined with a motion compensated signal yielding a combined signal. The combined signal is quantized into an output signal according to a quantization parameter, and the output signal is variable length encoded as a single layer bitstream. In a preprocessing step, the enhancement layer can be truncated according to rate control constraint, and the same constraints can also be used during the quantization.

Video transcoding of scalable multi-layer videos to single layer video

Media authentication is important in content delivery via untrusted intermediaries, such as peer-to-peer (P2P) file sharing. Many differently encoded versions of a media file might exist. Our previous work applied distributed source coding to distinguish the legitimate diversity of encoded images from tampering. An authentication decoder was supplied with a Slepian-Wolf encoded lossy version of the image as authentication data. Distributed source coding provided the desired robustness against legitimate encoding variations, while detecting illegitimate modification. We augment the decoder to localize tampering in an image already deemed to be unauthentic. The localization decoder requires only incremental localization data beyond the authentication data since we use rate-adaptive distributed source codes. Both decoders perform joint bitplane decoding, rather than conditional bitplane decoding. Our results demonstrate that tampered image blocks can be identified with high probability using authentication plus localization data of only a few hundred bytes for a 512times512 image.

/pdf/image-authentication-and-tampering-localization-using-3llrbcedms.pdf

Yao-Chung Lin

Papers

Image Authentication Based on Distributed Source Coding

Reduced-reference image quality assessment using distributed source coding

Image Authentication Using Distributed Source Coding

Video transcoding of scalable multi-layer videos to single layer video

Image Authentication and Tampering Localization using Distributed Source Coding