Logistic chaotic maps for binary numbers generations

Kanso, Ali; Smaoui, Nejib

doi:10.1016/j.chaos.2007.10.049

Cited by 222 publications

(115 citation statements)

References 35 publications

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“…Based on the above analysis, it can be seen that the randomness of the sequences generated via the CPNG and the RC4 algorithm do not have significant differences. Besides, we compare the results of the statistical tests with the results described in [6]. In [6], a pseudorandom binary sequence generator was proposed based on a combination of two logistic maps.…”

Section: Fips 140-2 Testmentioning

confidence: 99%

“…Besides, we compare the results of the statistical tests with the results described in [6]. In [6], a pseudorandom binary sequence generator was proposed based on a combination of two logistic maps. As a result it turned out that over 95% of the sequences passed the test of FIPS 140-2.…”

Section: Fips 140-2 Testmentioning

confidence: 99%

“…One way is to use a single chaotic map, such as Tent map [2], Henon map [3] and so on [4]- [5]. Another way is to extend or compound some common chaotic maps, such as Logistic map [6]- [7], Henon map [8]. By summarizing the literatures, it is found that the extension methods are simple addition, improved and coupled mostly.…”

Section: Introductionmentioning

confidence: 99%

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A Bidirectional Generalized Synchronization Theorem -Based Chaotic Pseudorandom Number Generator

Han

Lee

2013

TELKOMNIKA

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Keywords: sinkronisasi tergeneralisasi; urutan acak semu (pseudo-random sequence), tes FIPS-140-2, sistem diskret dua arah Abstract In order to design good pseudorandom number generator, using a bidirectional generalized synchronization theorem for discrete chaos system, this paper introduces a new 5-dimensional bidirectional generalized chaos synchronization system (BGCSDS), whose prototype is a novel chaotic system. Numerical simulation showed that two pair variables of the BGCSDS achieve generalized chaos synchronization via a transform H. A chaos-based pseudorandom number generator (CPNG) was designed by the new BGCSDS. Using the FIPS-140-2 tests issued by the National Institute of Standard and Technology (NIST) verified the randomness of the 1000 binary number sequences generated via the CPNG and the RC4 algorithm respectively. The results showed all the tested sequences passed the FIPS-140-2 tests. The confidence interval analysis showed the statistical properties of the randomness of the sequences generated via the CPNG and the RC4 algorithm do not have significant differences. So, the CPNG is suitable to be used in the information security filed.

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Section: Fips 140-2 Testmentioning

confidence: 99%

Section: Fips 140-2 Testmentioning

confidence: 99%

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A Bidirectional Generalized Synchronization Theorem -Based Chaotic Pseudorandom Number Generator

Han

Lee

2013

TELKOMNIKA

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“…The quasi-chaotic nonlinear filter was used in [12], and the piecewise linear chaotic map was used by Hasan [13] and Wang et al [14]. Logistic maps have been utilized in [15][16][17].…”

Section: Chaotic Logistic Mapmentioning

confidence: 99%

Improving the Diffusion of the Stream Cipher Salsa20 by Employing a Chaotic Logistic Map

Almazrooie¹,

Samsudin²,

Singh³

2015

J Inf Process Syst

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The stream cipher Salsa20 and its reduced versions are among the fastest stream ciphers available today. However, Salsa20/7 is broken and Salsa20/12 is not as safe as before. Therefore, Salsa20 must completely perform all of the four rounds of encryption to achieve a good diffusion in order to resist the known attacks. In this paper, a new variant of Salsa20 that uses the chaos theory and that can achieve diffusion faster than the original Salsa20 is presented. The method has been tested and benchmarked with the original Salsa20 with a series of tests. Most of the tests show that the proposed chaotic Salsa of two rounds is faster than the original four rounds of Salsa20/4, but it offers the same diffusion level.

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“…In recent years, chaotic systems were regarded as an important pseudorandom source in the design of random number generators [10][11][12]. As we know, chaotic systems may be attacked by phase space reconstruction and nonlinear prediction techniques.…”

Section: Maximum Entropy and Its Application In Cryptographymentioning

confidence: 99%