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Lossless generalized-LSB data embedding

IEEE TRANSACTIONS ON IMAGE PROCESSING 2005年第2期14卷 253-266页

作者： Celik, MU Sharma, G Tekalp, AM Saber, E Univ Rochester Dept Elect & Comp Engn Rochester NY 14627 USA Univ Rochester Dept Biostat & Computat Biol Rochester NY 14627 USA Koc Univ Coll Engn Istanbul Turkey Xerox Corp Webster NY 14580 USA

We present a novel lossless (reversible) data-embedding technique, which enables the exact recovery of the original host signal upon extraction of the embedded information. A generalization of the well-known least significant bit (LSB) modification is proposed as the data-embedding method, which introduces additional operating points on the capacity-distortion curve. Lossless recovery of the original is achieved by compressing portions of the signal that are susceptible to embedding distortion and transmitting these compressed descriptions as a part of the embedded payload. A prediction-based conditional entropy coder which utilizes unaltered portions of the host signal as side-information improves the compression efficiency and, thus, the lossless data-embedding capacity.

关键词： arithmetic coding conditional entropy coding context modeling data embedding data hiding least significant bit (LSB) modification watermark

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An algorithm for universal lossless compression with side information

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IEEE TRANSACTIONS ON INFORMATION THEORY 2006年第9期52卷 4008-4016页

作者： Cai, Haixiao Kulkarni, Sanjeev R. Verdu, Sergio Princeton Univ Dept Elect Engn Princeton NJ 08544 USA

This paper proposes a new algorithm based on the Context-Tree Weighting (CTW) method for universal compression of a finite-alphabet sequence x(1)(n) with side information y(1)(n) available to both the encoder and decoder. We prove that with probability one the compression ratio converges to the conditional entropy rate for jointly stationary ergodic sources. Experimental results with Markov chains and English texts show the effectiveness of the algorithm.

关键词： arithmetic coding conditional entropy context tree weighting method hidden Markov process source coding universal lossless data compression

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Context-Aware Linguistic Steganography Model Based on Neural Machine Translation

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IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING 2024年 32卷 868-878页

作者： Ding, Changhao Fu, Zhangjie Yang, Zhongliang Yu, Qi Li, Daqiu Huang, Yongfeng Nanjing Univ Informat Sci & Technol Engn Res Ctr Digital Forens Minist Educ Nanjing 210000 Peoples R China Xidian Univ Minist Educ State Key Lab Integrated Serv Networks Xian 710071 Peoples R China Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China

Linguistic steganography based on text generation is a hot topic in the field of text information hiding. Previous studies have managed to improve the syntactic quality of steganography texts using natural language processing techniques based on deep learning, but their steganography models still lack the ability to control the semantic and contextual characteristics in texts, which is caused by the shortage of relevant information they can obtain. This results in a great decline in the imperceptibility of steganographic texts. To address the problem, we propose a context-aware linguistic steganography method based on neural machine translation called NMT-Stega. The model generates translation containing secret messages based on the neural machine translation model with semantic fusion and language model reference units. In this way, the semantics and contexts of translation are controlled by the additional semantic and contextual features acquired from the text to be translated. Also, a new encoding that combines arithmetic coding with a waiting mechanism is proposed in our model. This method solves the low embedding capacity problem of waiting mechanism while ensuring the semantic and contextual characteristics of steganographic text are less modified. Experimental results show that our model outperforms the previous models and encoding methods in semantic correlation, embedding capacity and imperceptibility.

关键词： Neural networks linguistic steganography neural machine translation arithmetic coding

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THE CONTEXT-TREE WEIGHTING METHOD - BASIC PROPERTIES

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IEEE TRANSACTIONS ON INFORMATION THEORY 1995年第3期41卷 653-664页

作者： WILLEMS, FMJ SHTARKOV, YM TJALKENS, TJ Eindhoven University of Technology Electrical Engineering Department

We describe a sequential universal data compression procedure for binary tree sources that performs the ''double mixture.'' Using a context tree, this method weights in an efficient recursive way the coding distributions corresponding to all bounded memory tree sources, and achieves a desirable coding distribution for tree sources with an unknown model and unknown parameters, Computational and storage complexity of the proposed procedure are both linear in the source sequence length, We derive a natural upper bound on the cumulative redundancy of our method for individual sequences. The three terms in this bound can be identified as coding, parameter, and model redundancy, The bound holds for all source sequence lengths, not only for asymptotically large lengths, The analysis that leads to this bound is based on standard techniques and turns out to be extremely simple. Our upper bound on the redundancy shows that the proposed context-tree weighting procedure is optimal in the sense that it achieves the Rissanen (1984) lower bound.

关键词： SEQUENTIAL DATA COMPRESSION UNIVERSAL SOURCE coding TREE SOURCES MODELING PROCEDURE CONTEXT TREE arithmetic coding CUMULATIVE REDUNDANCY BOUNDS

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Texture- and multiple-template-based algorithm for lossless compression of error-diffused images

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2007年第5期16卷 1258-1268页

作者： Huang, Yong-Huai Chung, Kuo-Liang Natl Taiwan Univ Sci & Technol Dept Comp Sci & Informat Taipei 10672 Taiwan

Recently, several efficient context-based arithmetic coding algorithms have been developed successfully for lossless compression of error-diffused images. In this paper, we first present a novel block- and texture-based approach to train the multiple-template according to the most representative texture features. Based on the trained multiple template, we next present an efficient texture- and multiple-template-based (TM-based) algorithm for lossless compression of error-diffused images. In our proposed TM-based algorithm, the input image is divided into many blocks and for each block, the best template is adaptively selected from the multiple-template based on the texture feature of that block. Under 20 testing error-diffused images and the personal computer with Intel Celeron 2.8-GHz CPU, experimental results demonstrate that with a little encoding time degradation, 0.365 s (0.901 s) on average, the compression improvement ratio of our proposed TNI-based algorithm over the joint bilevel image group (JBIG) standard [over the previous block arithmetic coding for image compression (BACIC) algorithm proposed by Reavy and Boncelet is 24%] (19.4%). Under the same condition, the compression improvement ratio of our proposed algorithm over the previous algorithm by Lee and Park is 17.6% and still only has a little encoding time degradation (0.775 s on average). In addition, the encoding time required in the previous free tree-based algorithm is 109.131 s on average while our proposed algorithm takes 0.995 s;the average compression ratio of our proposed TM-based algorithm, 1.60, is quite competitive to that of the free tree-based algorithm, 1.62.

关键词： arithmetic coding context error-diffused images lossless compression multiple-template texture

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Design of new format for mass data compression

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The Journal of China Universities of Posts and Telecommunications 2011年第1期18卷 121-128页

作者： QIN Jian-cheng BAI Zhong-ying School of Computer Science Beijing University of Posts and Telecommunications Beijing 100876 China

In the field of lossless compression, most kinds of traditional software have some shortages when they face the mass data. Their compressing abilities are limited by the data window size and the compressing format design. This paper presents a new design of compressing format named ＇CZ format＇ which supports the data window size up to 4 GB and has some advantages in the mass data compression. Using this format, a compressing shareware named ＇ComZip＇ is designed. The experiment results support that ComZip has better compression ratio than WinZip, Bzip2 and are compressed. And ComZip has the potential to beat 7-zip in WinRAR in most cases, especially when GBs or TBs of mass data future as the data window size exceeds 128 MB.

关键词： mass data coding tossless compression LZ77/LZSS algorithm arithmetic coding

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Securing Multimedia Content Using Joint Compression and Encryption

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IEEE MULTIMEDIA 2013年第4期20卷 50-61页

作者： Pande, Amit Mohapatra, Prasant Zambreno, Joseph Univ Calif Davis Dept Comp Sci Davis CA 95616 USA Iowa State Univ Dept Elect & Comp Engn Ames IA USA

Algorithmic parameterization and hardware architectures can ensure secure transmission of multimedia data in resource-constrained environments such as wireless video surveillance networks, telemedicine frameworks for distant health care support in rural areas, and Internet video streaming. Joint multimedia compression and encryption techniques can significantly reduce the computational requirements of video processing systems. The authors present an approach to reduce the computational cost of multimedia encryption while also preserving the properties of compressed video. A hardware-amenable design of the proposed algorithms makes them suitable for real-time embedded multimedia systems. This approach alleviates the need for additional hardware for encryption in resource-constrained scenarios and can be otherwise used to augment existing encryption methods used for content delivery on the Internet or in other applications. This work shows how two compression blocks for video coding--a modified frequency transform (called a secure wavelet transform or SWT) and a modified entropy coding scheme (called a chaotic arithmetic coding or CAC)--can be used for video encryption. Experimental results are shown for selective encryption using the proposed schemes.

关键词： Encryption Content Analysis Discrete Wavelet Transforms Streaming Media Multimedia Communication Encoding arithmetic coding Multimedia Video Encryption Joint coding And Encryption Embedded Systems Discrete Wavelet Transform

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VLSI Architecture of arithmetic Coder Used in SPIHT

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IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS 2012年第4期20卷 697-710页

作者： Liu, Kai Belyaev, Evgeniy Guo, Jie Xidian Univ Comp Sch Xian 710071 Shaanxi Peoples R China Russian Acad Sci St Petersburg Inst Informat & Automat St Petersburg 199178 Russia Xidian Univ Commun Sch Xian 710071 Shaanxi Peoples R China

A high-throughput memory-efficient arithmetic coder architecture for the set partitioning in hierarchical trees (SPIHT) image compression is proposed based on a simple context model in this paper. The architecture benefits from various optimizations performed at different levels of arithmetic coding from higher algorithm abstraction to lower circuits' implementations. First, the complex context model used by software is mitigated by designing a simple context model, which just uses the brother nodes' states in the coding zerotree of SPIHT to form context symbols for the arithmetic coding. The simple context model results in a regular access pattern during reading the wavelet transform coefficients, which is convenient to the hardware implementation, but at a cost of slight performance loss. Second, in order to avoid rescanning the wavelet transform coefficients, a breadth first search SPIHT without lists algorithm is used instead of SPIHT with lists algorithm. Especially, the coding bit-planes of each zero tree are processed in parallel. Third, an out-of-order execution mechanism for different types of context is proposed that can allocate the context symbol to the idle arithmetic coding core with a different order that of the input. For the balance of the input rate of the wavelet coefficients, eight arithmetic coders are replicated in the compression system. And in one arithmetic coder, there exists four cores to process different contexts. Fourth, several dedicated circuits are designed to further improve the throughput of the architecture. The common bit detection (CBD) circuit is used for unrolling the renormalization stage of the arithmetic coding. The carry look-ahead adder (CLA) and fast multiplier-divider are also employed to shorten the critical path in the architecture. Moreover, an adaptive clock switch mechanism can stop some invalid bit-planes' clock for the power saving purpose according to the input images. Experimental results demonstrate that the p

关键词： arithmetic coding common bit detection (CBD) circuit context model out-of-order execution set partitioning in hierarchical trees (SPIHT) VLSI arithmetic coder architecture

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Iterative decoding of serially concatenated arithmetic and channel codes with JPEG 2000 applications

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2007年第6期16卷 1557-1567页

作者： Grangetto, Marco Scanavino, Bartolo Olmo, Gabriella Benedetto, Sergio Politecn Torino Dept Elect Ctr Multimedia Radio Commun CERCOM I-10129 Turin Italy

In this paper, an innovative joint-source channel coding scheme is presented. The proposed approach enables iterative soft decoding of arithmetic codes by means of a soft-in soft- out decoder based on suboptimal search and pruning of a binary tree. An error-resilient arithmetic coder with a forbidden symbol is used in order to improve the performance of the joint source/channel scheme. The performance in the case of transmission across the AWGN channel is evaluated in terms of word error probability and compared to a traditional separated approach. The interleaver gain, the convergence property of the system, and the optimal source/channel rate allocation are investigated. Finally, the practical relevance of the proposed joint decoding approach is demonstrated within the JPEG 2000 coding standard. In particular, an iterative channel and JPEG 2000 decoder is designed and tested in the case of image transmission across the AWGN channel.

关键词： arithmetic coding iterative decoding joint-source channel coding (JSCC) JPEG 2000 MAP decoding

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Cover Reproducible Steganography via Deep Generative Models

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IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING 2023年第5期20卷 3787-3798页

作者： Chen, Kejiang Zhou, Hang Wang, Yaofei Li, Menghan Zhang, Weiming Yu, Nenghai Univ Sci & Technol China CAS Key Lab Electrospace Informat Sch Cyber Sci & Technol Anhui Prov Key Lab Cyberspace Secur Situat Aware Hefei 230026 Anhui Peoples R China Simon Fraser Univ Sch Comp Sci Burnaby BC V5A 1S6 Canada Hefei Univ Technol Sch Comp Sci Hefei 230002 Anhui Peoples R China

Whereas cryptography easily arouses attacks by means of encrypting a secret message into a suspicious form, steganography is advantageous for its resilience to attacks by concealing the message in an innocent-looking cover signal. Minimal distortion steganography, one of the mainstream steganography frameworks, embeds messages while minimizing the distortion caused by the modification on the cover elements. Due to the unavailability of the original cover signal for the receiver, message embedding is realized by finding the coset leader of the syndrome function of steganographic codes migrated from channel coding, which is complex and has limited performance. Fortunately, deep generative models and the robust semantic of generated data make it possible for the receiver to perfectly reproduce the cover signal from the stego signal. With this advantage, we propose cover-reproducible steganography where the source coding, e.g., arithmetic coding, serves as the steganographic code. Specifically, the decoding process of arithmetic coding is used for message embedding and its encoding process is regarded as message extraction. Taking text-to-speech and text-to-image synthesis tasks as two examples, we illustrate the feasibility of cover-reproducible steganography. Steganalysis experiments and theoretical analysis are conducted to demonstrate that the proposed methods outperform the existing methods in most cases.

关键词： Steganography Distortion Encoding Receivers Codes Costs Task analysis Steganography reproducible arithmetic coding text-to-speech text-to-image generative model

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