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This paper investigates compression of data encrypted with block ciphers, such as the Advanced Encryption Standard (AES). It is shown that such data can be feasibly compressed without knowledge of the secret key. Block ciphers operating in…

Information Theory · Computer Science 2010-09-10 Demijan Klinc , Carmit Hazay , Ashish Jagmohan , Hugo Krawczyk , Tal Rabin

This paper describes a new method of data encoding which may be used in various modern digital, computer and telecommunication systems and devices. The method permits the compression of data for storage or transmission, allowing the exact…

Information Theory · Computer Science 2012-01-27 Igor Nesiolovskiy , Artem Nesiolovskiy

In prefix coding over an infinite alphabet, methods that consider specific distributions generally consider those that decline more quickly than a power law (e.g., Golomb coding). Particular power-law distributions, however, model many…

Information Theory · Computer Science 2009-03-06 Michael B. Baer

Most of the attention in statistical compression is given to the space used by the compressed sequence, a problem completely solved with optimal prefix codes. However, in many applications, the storage space used to represent the prefix…

Data Structures and Algorithms · Computer Science 2015-06-30 Travis Gagie , Gonzalo Navarro , Yakov Nekrich , Alberto Ordóñez

Many proofs in discrete mathematics and theoretical computer science are based on the probabilistic method. To prove the existence of a good object, we pick a random object and show that it is bad with low probability. This method is…

Information Theory · Computer Science 2017-08-01 Pat Morin , Wolfgang Mulzer , Tommy Reddad

In this paper we consider the use of variable length non prefix-free codes for coding constrained sequences of symbols. We suppose to have a Markov source where some state transitions are impossible, i.e. the stochastic matrix associated…

Information Theory · Computer Science 2007-07-16 Marco Dalai , Riccardo Leonardi

A new class of folded subspace codes for noncoherent network coding is presented. The codes can correct insertions and deletions beyond the unique decoding radius for any code rate $R\in[0,1]$. An efficient interpolation-based decoding…

Information Theory · Computer Science 2015-04-22 Hannes Bartz , Vladimir Sidorenko

This paper proposed the application of post-encryption-compression (PEC) to strengthen the secrecy in the case of distributed encryption where the encryption keys are correlated to each other. We derive the universal code construction for…

Information Theory · Computer Science 2018-01-17 Bagus Santoso , Yasutada Oohama

We present shuffle coding, a general method for optimal compression of sequences of unordered objects using bits-back coding. Data structures that can be compressed using shuffle coding include multisets, graphs, hypergraphs, and others. We…

Machine Learning · Computer Science 2024-08-19 Julius Kunze , Daniel Severo , Giulio Zani , Jan-Willem van de Meent , James Townsend

Many data compressors regularly encode probability distributions for entropy coding - requiring minimal description length type of optimizations. Canonical prefix/Huffman coding usually just writes lengths of bit sequences, this way…

Information Theory · Computer Science 2022-07-05 Jarek Duda

Constrained coding plays a key role in optimizing performance and mitigating errors in applications such as storage and communication, where specific constraints on codewords are required. While non-parametric constraints have been…

Information Theory · Computer Science 2025-05-05 Daniella Bar-Lev , Michael Shlizerman

In this article we focus on the problem of channel decoding in presence of a-priori information. In particular, assuming that the a-priori information reliability is not perfectly estimated at the receiver, we derive a novel analytical…

Information Theory · Computer Science 2007-11-14 Andrea Abrardo

Consider the case where consecutive blocks of N letters of a semi-infinite individual sequence X over a finite-alphabet are being compressed into binary sequences by some one-to-one mapping. No a-priori information about X is available at…

Information Theory · Computer Science 2013-01-25 Jacob Ziv

Large alphabet source coding is a basic and well-studied problem in data compression. It has many applications such as compression of natural language text, speech and images. The classic perception of most commonly used methods is that a…

Information Theory · Computer Science 2016-07-26 Amichai Painsky , Saharon Rosset , Meir Feder

This paper describes a new set of block source codes well suited for data compression. These codes are defined by sets of productions rules of the form a.l->b, where a in A represents a value from the source alphabet A and l, b are -small-…

Information Theory · Computer Science 2009-09-29 Herve Jegou , Christine Guillemot

Most of the world's digital data is currently encoded in a sequential form, and compression methods for sequences have been studied extensively. However, there are many types of non-sequential data for which good compression techniques are…

Information Theory · Computer Science 2016-01-15 Christian Steinruecken

There is a class of entropy-coding methods which do not substitute symbols by code words (such as Huffman coding), but operate on intervals or ranges. This class includes three prominent members: conventional arithmetic coding, range…

Information Theory · Computer Science 2025-07-04 Tilo Strutz , Nico Schreiber

Universal fixed-to-variable lossless source coding for memoryless sources is studied in the finite blocklength and higher-order asymptotics regimes. Optimal third-order coding rates are derived for general fixed-to-variable codes and for…

Information Theory · Computer Science 2014-12-16 Oliver Kosut , Lalitha Sankar

This paper proposes a novel entropy encoding technique for lossless data compression. Representing a message string by its lexicographic index in the permutations of its symbols results in a compressed version matching Shannon entropy of…

Information Theory · Computer Science 2017-03-24 Abu Bakar Siddique

We describe a method for lossless quantum compression if the output of the information source is not known. We compute the best possible compression rate, minimizing the expected base length of the output quantum bit string (the base length…

Quantum Physics · Physics 2009-01-19 Markus Mueller , Caroline Rogers , Rajagopal Nagarajan
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