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Statistical Techniques for Language Recognition: An Introduction and Guide for Cryptanalysts
 Cryptologia
, 1993
"... We explain how to apply statistical techniques to solve several languagerecognition problems that arise in cryptanalysis and other domains. Language recognition is important in cryptanalysis because, among other applications, an exhaustive key search of any cryptosystem from ciphertext alone requir ..."
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Cited by 12 (2 self)
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We explain how to apply statistical techniques to solve several languagerecognition problems that arise in cryptanalysis and other domains. Language recognition is important in cryptanalysis because, among other applications, an exhaustive key search of any cryptosystem from ciphertext alone requires a test that recognizes valid plaintext. Written for cryptanalysts, this guide should also be helpful to others as an introduction to statistical inference on Markov chains. Modeling language as a finite stationary Markov process, we adapt a statistical model of pattern recognition to language recognition. Within this framework we consider four welldefined languagerecognition problems: 1) recognizing a known language, 2) distinguishing a known language from uniform noise, 3) distinguishing unknown 0thorder noise from unknown 1storder language, and 4) detecting nonuniform unknown language. For the second problem we give a most powerful test based on the NeymanPearson Lemma. For the oth...
On the Properties of Pseudo Noise Sequences with a Simple Proposal of Randomness Test
"... Abstract—Maximal length sequences (msequences) are also known as pseudo random sequences or pseudo noise sequences for closely following Golomb’s popular randomness properties: (P1) balance, (P2) run, and (P3) ideal autocorrelation. Apart from these, there also exist certain other less known proper ..."
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Cited by 1 (0 self)
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Abstract—Maximal length sequences (msequences) are also known as pseudo random sequences or pseudo noise sequences for closely following Golomb’s popular randomness properties: (P1) balance, (P2) run, and (P3) ideal autocorrelation. Apart from these, there also exist certain other less known properties of such sequences all of which are discussed in this tutorial paper. Comprehensive proofs to each of these properties are provided towards better understanding of such sequences. A simple test is also proposed at the end of the paper in order to distinguish pseudo noise sequences from truly random sequences such as Bernoulli sequences. Keywords—Maximal length sequence, pseudo noise sequence, punctured de Bruijn sequence, autocorrelation, Bernoulli sequence, randomness tests. I.
International Journal of Electrical and Computer Engineering 3:3 2008 On the Properties of Pseudo Noise Sequences with a Simple Proposal of Randomness Test
"... Abstract—Maximal length sequences (msequences) are also known as pseudo random sequences or pseudo noise sequences for closely following Golomb’s popular randomness properties: (P1) balance, (P2) run, and (P3) ideal autocorrelation. Apart from these, there also exist certain other less known proper ..."
Abstract
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Abstract—Maximal length sequences (msequences) are also known as pseudo random sequences or pseudo noise sequences for closely following Golomb’s popular randomness properties: (P1) balance, (P2) run, and (P3) ideal autocorrelation. Apart from these, there also exist certain other less known properties of such sequences all of which are discussed in this tutorial paper. Comprehensive proofs to each of these properties are provided towards better understanding of such sequences. A simple test is also proposed at the end of the paper in order to distinguish pseudo noise sequences from truly random sequences such as Bernoulli sequences. Keywords—Maximal length sequence, pseudo noise sequence, punctured de Bruijn sequence, autocorrelation, Bernoulli sequence, randomness tests. I.
Is the Data Encryption Standard a Group? (Results of Cycling Experiments on DES)I
"... Abstract. The Data Encryption Standard (DES) defines an indexed set of permutations acting on the message space ~ = {0, 1} 64. If this set of permutations were closed under functional composition, then the two most popular proposals for strengthening DES through multiple encryption would be equival ..."
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Abstract. The Data Encryption Standard (DES) defines an indexed set of permutations acting on the message space ~ = {0, 1} 64. If this set of permutations were closed under functional composition, then the two most popular proposals for strengthening DES through multiple encryption would be equivalent to single encryption. Moreover, DES would be vulnerable to a knownplaintext attack that runs in 22s steps on the average. It is unknown in the open literature whether or not DES has this weakness. Two statistical tests are presented for determining if an indexed set of permutations acting on a finite message space forms a group under functional composition. The first test is a "meetinthemiddle " algorithm which uses O(v/K) time and space, where K is the size of the key space. The second test, a novel cycling algorithm, uses the same amount of time but only a small constant amount of space. Each test yields a knownplaintext attack against any finite, deterministic cryptosystem that generates a small group. The cycling closure test takes a pseudorandom walk in the message space until