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CHEATING DETECTION AND CHEATER IDENTIFICATION IN SECRET SHARING SCHEMES

IEE PROCEEDINGS-COMPUTERS AND DIGITAL TECHNIQUES 1995年第5期142卷 367-369页

作者： WU, TC WU, TS Dept. of Ind. Manage. Nat. Taiwan Inst. of Technol. Taipei Taiwan

A threshold scheme for secret sharing can protect a secret with high reliability and flexibility. These advantages can be achieved only when all the participants are honest, i.e. all the participants willing to pool their shadows shall always present the true ones. Cheating detection is an important issue in the secret sharing scheme. However, cheater identification is more effective than cheating detection in realistic applications. If some dishonest participants exist, the other honest participants will obtain a false secret, while the cheaters may individually obtain the true one. The paper presents a method to enforce the security of any threshold scheme with the ability to detect cheating and identify cheaters. By applying a one-way hashing function along with the use of arithmetic coding, the proposed method can be used to deterministically detect cheating and identify the cheaters, no matter how many cheaters are involved in the secret reconstruction.

关键词： arithmetic coding CHEATING INTERPOLATING POLYNOMIAL ONE-WAY HASHING FUNCTION SECRET SHARING

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Simple lossless preprocessing algorithms for text compression

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IET SOFTWARE 2009年第1期3卷 37-45页

作者： Robert, L. Nadarajan, R. Govt Arts Coll Dept Comp Sci Coimbatore Tamil Nadu India PSG Coll Technol Dept Comp Applicat Coimbatore Tamil Nadu India

Lossless data compression researchers have developed highly sophisticated approaches, such as Huffman encoding, arithmetic coding, the Lempel-Ziv family, prediction by partial matching and Burrow-Wheeler transform based algorithms. One approach for attaining better compression is to develop generic, reversible transformation that can be applied to a source text that improves an existing compression algorithm's ability to compress. A few reversible transformation techniques that give better compression ratios are presented. A method, which transforms a text file into intermediate file with minimum possible byte values, is proposed. An attempt has been made to reduce the number of possible bytes that appear after every byte in the source file. This increases backend algorithm's compression performance.

关键词： lossless data compression Lempel-Ziv family text compression data compression arithmetic coding arithmetic codes transform coding Huffman codes lossless preprocessing algorithms text analysis Burrow-Wheeler transform Document processing techniques Huffman encoding

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Lossless compression algorithms for smart cards: A progress report

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 1997年第1期13卷 27-38页

作者： Dhem, JF Quisquater, JJ UNIV CATHOLIQUE LOUVAIN MICROELECT LAB B-1348 LOUVAIN BELGIUM

We first describe how data compression can be suitable for the smart card context. After looking at the different models of compressor, we choose the best suited for smart cards at the present time: the static lossless compressor, mainly the Huffman and the arithmetic. The static Huffman algorithm we implemented and the memory size needed for a smart card implementation are detailed. Thereafter, the first experimental results we obtain on some typical files permit to conclude that our compressor is implementable in smart cards. This paper opens up the way to a new approach of data compression algorithms for small files using very small resources. This work is still in progress.

关键词： static lossless compression smart cards Huffman coding arithmetic coding

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On Nonlinear Compression Costs: When Shannon Meets Renyi

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IEEE ACCESS 2024年 12卷 77750-77763页

作者： Somazzi, Andrea Ferragina, Paolo Garlaschelli, Diego IMT Sch Adv Studies Lucca I-55100 Lucca Italy Scuola Normale Super Pisa I-56126 Pisa Italy Univ Pisa Dept Comp Sci I-56127 Pisa Italy Lorentz Inst Theoret Phys NL-2333 CA Leiden Netherlands INdAM GNAMPA Ist Nazl Alta Matemat I-00185 Rome Italy

In compression problems, the minimum average codeword length is achieved by Shannon entropy, and efficient coding schemes such as arithmetic coding (AC) achieve optimal compression. In contrast, when minimizing the exponential average length, R & eacute;nyi entropy emerges as a compression lower bound. This paper presents a novel approach that extends and applies the AC model to achieve results that are arbitrarily close to R & eacute;nyi's lower bound. While rooted in the theoretical framework assuming independent and identically distributed symbols, the empirical testing of this generalized AC model on a Wikipedia dataset with correlated symbols reveals significant performance enhancements over its classical counterpart, when considering the exponential average. The paper also demonstrates an intriguing equivalence between minimizing the exponential average and minimizing the likelihood of exceeding a predetermined threshold in codewords' length. An extensive experimental comparison between generalized and classical AC unveils a remarkable reduction, by several orders of magnitude, in the fraction of codewords surpassing the specified threshold in the Wikipedia dataset.

关键词： Symbols Channel coding Entropy Costs arithmetic Europe Data compression Codes arithmetic coding Campbell theorem large deviations R & eacute nyi entropy

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Boosting textual compression in optimal linear time

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JOURNAL OF THE ACM 2005年第4期52卷 688-713页

作者： Ferragina, P Giancarlo, R Manzini, G Sciortino, M Univ Pisa Dipartimento Informat I-56127 Pisa Italy Univ Palermo I-90133 Palermo Italy Univ Piemonte Orientale Alessandria Italy

We provide a general boosting technique for Textual Data Compression. Qualitatively, it takes a good compression algorithm and turns it into an algorithm with a better compression performance guarantee. It displays the following remarkable properties: (a) it can turn any memoryless compressor into a compression algorithm that uses the "best possible" contexts;(b) it is very simple and optimal in terms of time;and (c) it admits a decompression algorithm again optimal in time. To the best of our knowledge, this is the first boosting technique' displaying these properties. Technically, our boosting technique builds upon three main ingredients: the Burrows-Wheeler Transform, the Suffix Tree data structure, and a greedy algorithm to process them. Specifically, we show that there exists a proper partition of the Burrows-Wheeler Transform of a string s that shows a deep combinatorial relation with the kth order entropy of s. That partition can be identified via a greedy processing of the suffix tree of s with the aim of minimizing a proper objective function over its nodes. The final compressed string is then obtained by compressing individually each substring of the partition by means of the base compressor we wish to boost. Our boosting technique is inherently combinatorial because it does not need to assume any prior probabilistic model about the source emitting s, and it does not deploy any training, parameter estimation and learning. Various corollaries are derived from this main achievement. Among the others, we show analytically that using our booster, we get better compression algorithms than some;of the best existing ones, that is, LZ77, LZ78, PPMC and the ones derived from the Burrows-Wheeler Transform. Further, we settle analytically some long-standing open problems about the algorithmic structure and the performance of BWT-based compressors. Namely, we provide the first family of BWT algorithms that do not use Move-To-Front or Symbol Ranking as a part of the co

关键词： algorithms design theory arithmetic coding Burrows-Wheeler transform empirical entropy Huffman coding Lempel-Ziv compressors suffix tree text compression

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Analysis of the Limitations of Further Improvement of the Efficiency of VVC-CABAC

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IEEE ACCESS 2023年 11卷 16793-16800页

作者： Karwowski, Damian Domanski, Marek Peng, Wen-Hsiao Hang, Hsueh-Ming Poznan Univ Tech Fac Comp & Telecommun PL-60965 Poznan Poland Natl Yang Ming Chiao Tung Univ Inst Data Sci Hsinchu 30010 Taiwan Natl Yang Ming Chiao Tung Univ Inst Elect Hsinchu 30010 Taiwan

Hybrid video compression plays an invaluable role in digital video transmission and storage services and systems. It performs several-hundred-fold reduction in the amount of video data, which makes these systems much more efficient. An important element of hybrid video compression is entropy coding of the data. The state-of-the-art in this field is the newest variant of the Context-based Adaptive Binary arithmetic coding entropy compression algorithm which recently became part of the new Versatile Video coding technology. This work is a part of research that is currently underway to further improve the Context-based Adaptive Binary arithmetic coding technique. This paper provides analysis of the potential for further improvement of the Context-based Adaptive Binary arithmetic coding technique by more accurate calculation of probabilities of data symbols. The mentioned technique calculates those probabilities by the use of idea of the two-parameters hypothesis. For the needs of analysis presented in this paper, an extension of the aforementioned idea was proposed which consists of three- and four-parameters hypothesis. In addition, the paper shows the importance of proper calibration of parameter values of the method on efficiency of data compression. Results of experiments show that for the considered in the paper variants of the algorithm improvement the possible efficiency gain is at levels 0.11% and 0.167%, for the three- and four-parameter hypothesis, respectively.

关键词： Streaming media Estimation Probability Syntactics Symbols Entropy coding arithmetic Video compression Probability estimation entropy coding arithmetic coding VVC-CABAC video compression

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Fast adaptive arithmetic code for large alphabet sources with asymmetrical distributions

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IEEE COMMUNICATIONS LETTERS 2003年第1期7卷 33-35页

作者： Ryabko, B Rissanen, J Siberian State Univ Telecommun & Comp Sci Novosibirsk 630102 Russia Tampere Univ Technol FIN-33101 Tampere Finland

We address the problem of constructing an adaptive arithmetic code in the case where the source alphabet is large and there are lots of different symbols with equal counts of occurrence. For an alphabet of N symbols and r distinct symbol weights we describe a code for which the number of operations needed for encoding and decoding is equal to c log r+c(1) instead of c log N+c(2) as in previous arithmetic codes, c, c(1), c(2) are constants. When r is small relative to N-which is the case for most practical coding problems on large alphabets-the encoding and decoding speed of the suggested code will be substantially greater than with known methods.

关键词： adaptive algorithm arithmetic coding cumulative probabilities data compression fast algorithms source coding

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Adaptive probability estimation based on IIR filtering method

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ELECTRONICS LETTERS 2002年第25期38卷 1659-1660页

作者： Kruger, D Penzhorn, WT Univ Pretoria Dept Elect Elect & Comp Engn ZA-0002 Pretoria South Africa

A technique for adaptive estimation of source symbol probabilities is introduced, based on an infinite impulse response (IIR) filtering method. Symbol probabilities are estimated efficiently by means of exponential weighting, and used in conjunction with arithmetic coding. Experimental results indicate that better compression is achieved than with other comparable probability estimation methods.

关键词： Simulation, modelling and identification adaptive probability estimation arithmetic codes compression Digital signal processing filtering theory data compression IIR filtering Codes adaptive estimation probability arithmetic coding infinite impulse response filtering exponential weighting Other topics in statistics Filtering methods in signal processing IIR filters adaptive filters symbol probability

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Intra-Frame Compression of Point Cloud Geometry Using Dyadic Decomposition

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IEEE SIGNAL PROCESSING LETTERS 2020年第0期27卷 246-250页

作者： Peixoto, Eduardo Univ Brasilia Dept Elect Engn BR-70910900 Brasilia DF Brazil

This letter presents a lossless intra coder of the geometry information of voxelized point clouds. Instead of using the popular octree decomposition, the proposed method views the point cloud geometry as an array of bi-level images, and it is inspired by well-known techniques for coding this type of images. This array is encoded using a dyadic decomposition that recursively splits the array into two arrays of half its size, transmitting the occupancy information of each smaller array. Context adaptive arithmetic coding, using both 2D and 3D contexts, is used to achieve efficient compression. Results show that the proposed method outperforms all state-of-the-art intra coders on the public available point cloud datasets tested.

关键词： Point clouds intra coder lossless coding arithmetic coding

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Compaction of RFID Devices Using Data Compression

IEEE JOURNAL OF RADIO FREQUENCY IDENTIFICATION

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IEEE JOURNAL OF RADIO FREQUENCY IDENTIFICATION 2017年第3期1卷 202-207页

作者： Wiseman, Yair Bar Ilan Univ Comp Sci Dept IL-52900 Ramat Gan Israel

When a coding system used to represent letters or numbers in transmitting messages has many unused codewords, it will be more than reasonable to compress the messages. Electronic product code (EPC) which is widely used by many RFID devices has plentiful unused codewords. As a matter of fact, the unused codewords are most by far of the codewords. In this paper, we check the suitableness of a commonly used compression algorithm for EPC of RFID devices.

关键词： Huffman coding RFID tags Compression algorithms Product codes Compaction Data compression RFID electronic product code (EPC) compression arithmetic coding

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