Analysis of cellular automata used as pseudorandom pattern generators

Bardell, P.H.

doi:10.1109/test.1990.114093

Cited by 80 publications

(27 citation statements)

References 5 publications

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“…The reverse problem of finding a CA for a given polynomial was open for several years [1,7], and was solved (for GF(2) only) independently for irreducible polynomials by [2,9]. Both authors give a proof of existence, a proof of uniqueness (up to rule reversal), and an algorithm (the algorithms are quite different but have the same order of complexity).…”

Section: Academic Pressmentioning

confidence: 99%

An Explicit Similarity Transform between Cellular Automata and LFSR Matrices

Cattell

Muzio

1998

Finite Fields and Their Applications

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This paper demonstrates a similarity transform between the tridiagonal matrices of one-dimensional linear hybrid cellular automata and the companion matrices of linear feedback shift registers. Such a transform is of interest to the VLSI design community, as it provides an explicit mapping between the states of these two linear finite state machines. Academic PressA one-dimensional linear hybrid cellular automata (CA) is a linear finite state machine used in VLSI for test pattern generation and signature analysis. As well as their practical applications, these machines have proved to have fascinating theoretical properties, one of which is the relationship between a CA and its characteristic polynomial. One facet of this relationship is the similarity transform between a CA and its corresponding linear feedback shift register (LFSR).Given a CA, it is easy to find its (unique) characteristic polynomial. The reverse problem of finding a CA for a given polynomial was open for several years [1,7], and was solved (for GF(2) only) independently for irreducible polynomials by [2,9]. Both authors give a proof of existence, a proof of uniqueness (up to rule reversal), and an algorithm (the algorithms are quite different but have the same order of complexity).The transform presented here does not solve any of the above problems, as it relies on knowing the CA in advance. Rather, given the above results, it

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Section: Academic Pressmentioning

confidence: 99%

An Explicit Similarity Transform between Cellular Automata and LFSR Matrices

Cattell

Muzio

1998

Finite Fields and Their Applications

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“…This attack works on a PC with values of n up to 500 bits. Additionally, Paul Bardell proved that the output of a cellular automaton can also be generated by a linear-feedback shift register of equal length and is therefore no more secure [83].…”

Section: Cellular Automaton Generatormentioning

confidence: 99%

Applied cryptography: Protocols, algorithms, and source code in C

1994

Computer Law & Security Review

771

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“…In MaxCA, the generation procedure of PPS free random pattern is complex. In this methodology, it is mandatory to keep track of PPS in maximum length cycle and to exclude this portion in resulting maximum length cycle [7][8][9][10][11][12][13][14]. The associated cost should be increased for generation of pseudorandom patterns using a single cycle with larger numbers of states.…”

Section: Introductionmentioning

confidence: 99%

Random number generators: performance comparison of ELCA and MaxCA

Mitra

Kundu

Das

2014

CSIT

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In this paper, we have compared the performances of different cellular automata based random number generators to emphasize on the quality of randomness with a focus on cost effectiveness for concerned fault coverage. This research includes the study of maximum length cellular automata random number generator and proposed equal length cellular automata random number generator. It is found from the experimental results that resulting sequences have significant improvement in terms of randomness quality and associated fault coverage in their generation procedures. The different complexities associated considered here for generation of random numbers, are: space complexity, time complexity, design complexity and searching complexity.

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Analysis of cellular automata used as pseudorandom pattern generators

Cited by 80 publications

References 5 publications

An Explicit Similarity Transform between Cellular Automata and LFSR Matrices

An Explicit Similarity Transform between Cellular Automata and LFSR Matrices

Applied cryptography: Protocols, algorithms, and source code in C

Random number generators: performance comparison of ELCA and MaxCA

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