Robust PRNG based on homogeneously distributed chaotic dynamics

Garasym, Oleg; Lozi, René; Taralova, Ina

doi:10.1088/1742-6596/692/1/012011

Cited by 13 publications

(11 citation statements)

References 12 publications

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“…Convert the sequence X from decimalism to binary elements first, then separate it into 100 bit streams. So, each bit stream contains 3125000×32/100=10 6 bits. After that, we calculate the number of 0 and 1 in each bit stream.…”

Section: Uniformity Test In Binary Levelmentioning

confidence: 99%

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Efficient Pseudo-chaotic Number Generator for Cryptographic Applications

Qiao¹,

Taralova²,

Assad³

2020

IJICR

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A secure and efficient pseudo-random number generator is crucial for the security of a stream cipher or block cipher in a cryptosystem. This paper is devoted to the design and analysis of a new robust Pseudo-Chaotic Number Generator (PCNG) based on discrete chaotic maps over a finite field, and a multiplexing mechanism. The proposed PCNG contains three discrete chaotic maps: Piece-Wise Linear Chaotic Map (PWLCM), skew tent and logistic map. XOR operators are applied on these maps to form three optional intermediate outputs that are selected by the multiplexing mechanism to produce the final pseudo-chaotic sequence. The XOR operators and multiplexing mechanism can increase the dynamic pseudo-chaotic properties significantly. The PCNG is designed over a finite 2 32 field, has a simple structure and can be easily implemented. It has been implemented on a new stream cipher. Security analyses and statistical experiments have been carried out and the results have proven that the proposed PCNG can generate effective pseudorandom numbers and the stream cipher exhibits good security properties with large secret key space and high key sensitivity. Therefore, the proposed PCNG can be successfully applied in cryptosystems.

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Section: Uniformity Test In Binary Levelmentioning

confidence: 99%

“…A chaotic coupling method with topology network was explored to design two robust PCNGs based on tent and logistic maps [6]. R. Lozi brought out a weak coupling approach to hide the chaotic functions and enhance the chaotic generators [7].…”

Section: Introductionmentioning

confidence: 99%

Efficient Pseudo-chaotic Number Generator for Cryptographic Applications

Qiao¹,

Taralova²,

Assad³

2020

IJICR

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“…Since, complex (e.g. chaotic) behavior can be exhibited even by some piece-wise linear (PWL) maps [5,6,9,10,12]. It makes them particularly attractive for different real life applications such as Secure Communications, Information Encryption or Secure Electronic Transactions.…”

Section: Chaotic Generator To Create Accountsmentioning

confidence: 99%

A Novel Approach for Protection of Accounts’ Names against Hackers Combining Cluster Analysis and Chaotic Theory

Andreev¹,

Petrakieva²,

Taralova³

2018

JITST

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The last years of the 20 th century and the beginning of the 21 th mark the facilitation trend of our real life due to the big development and progress of the computers and other intelligent devices. Algorithms based on artificial intelligence are basically a part of the software. The transmitted information by Internet or LAN arises continuously and it is expected that the protection of the data has been ensured.The aim of the present paper is to reveal false names of users' accounts as a result of hackers' attacks. The probability a given account to be either false or actual is calculated using a novel approach combining machine learning analysis (especially clusters' analysis) with chaos theory. The suspected account will be used as a pattern and by classification techniques clusters will be formed with a respective probability this name to be false. This investigation puts two main purposes: First, to determine if there exists a trend of appearance of the similar usernames, which arises during the creation of new accounts. Second, to detect the false usernames and to discriminate those from the real ones, independently of that if two types of accounts are generated with the same speed.These security systems are applied in different areas, where the security of the data in users' accounts is strictly required. For example, they can be used in on-line voting for balloting, in studying the social opinion by inquiries, in protection of the information in different user accounts of given system etc.

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“…Recently, Lozi et al proposed innovative methods in order to increase randomness properties of the tent and logistic maps over their coupling and sub-sampling [31][32][33]. Nowadays, hundreds of publications on industrial applications of chaosbased cryptography are available [34][35][36][37].…”

Section: Tent-logistic Entangled Mapmentioning

confidence: 99%

The Challenging Problem of Industrial Applications of Multicore-Generated Iterates of Nonlinear Mappings

Lozi

Garasym²,

Lozi

2017

Industrial Mathematics and Complex Systems

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The study of nonlinear dynamics is relatively recent with respect to the long historical development of early mathematics since the Egyptian and the Greek civilization, even if one includes in this field of research the pioneer works of Gaston Julia and Pierre Fatou related to one-dimensional maps with a complex variable, nearly a century ago. In France, Igor Gumosky and Christian Mira began their mathematical researches in 1958; in Japan, the Hayashi' School (with disciples such as Yoshisuke Ueda and Hiroshi Kawakami), a few years later, was motivated by applications to electric and electronic circuits. In Ukraine, Alexander Sharkovsky found the intriguing Sharkovsky's order, giving the periods of periodic orbits of such nonlinear maps in 1962, although these results were only published in 1964. In 1983, Leon O. Chua invented a famous electronic circuit that generates chaos, built with only two capacitors, one inductor and one nonlinear negative resistance. Since then, thousands of papers have been published on the general topic of chaos. However, the pace of mathematics is slow, because any progress is based on strictly rigorous proof. Therefore, numerous problems still remain unsolved. For example, the long-term dynamics of the Hénon map, the first example of a strange attractor for mappings, remain unknown close to the classical parameter values from a strictly mathematical point of view, 40 years after its original publication. In spite of this lack of rigorous mathematical proofs, nowadays, engineers are actively working on applications of chaos for several purposes: global optimization, genetic algorithms, CPRNG (Chaotic Pseudorandom Number Generators), cryptography, and so on. They use nonlinear maps for practical applications without the need of sophisticated theorems. In this chapter, after giving some prototypical examples of the industrial

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Robust PRNG based on homogeneously distributed chaotic dynamics

Cited by 13 publications

References 12 publications

Efficient Pseudo-chaotic Number Generator for Cryptographic Applications

Efficient Pseudo-chaotic Number Generator for Cryptographic Applications

A Novel Approach for Protection of Accounts’ Names against Hackers Combining Cluster Analysis and Chaotic Theory

The Challenging Problem of Industrial Applications of Multicore-Generated Iterates of Nonlinear Mappings

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