scholarly journals A Lightweight BCH Code Corrector of TRNG with Measurable Dependence

2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Hojoong Park ◽  
Yongjin Yeom ◽  
Ju-Sung Kang
Keyword(s):  
Linear Code ◽  
Random Number ◽  
Random Number Generator ◽  
The Other ◽  
Bch Code ◽  
Compression Rate ◽  
Number Generator ◽  
Von Neumann ◽  
Other Hand ◽  
Cryptographic Algorithms

We propose a new lightweight BCH code corrector of the random number generator such that the bitwise dependence of the output value is controllable. The proposed corrector is applicable to a lightweight environment and the degree of dependence among the output bits of the corrector is adjustable depending on the bias of the input bits. Hitherto, most correctors using a linear code are studied on the direction of reducing the bias among the output bits, where the biased input bits are independent. On the other hand, the output bits of a linear code corrector are inherently not independent even though the input bits are independent. However, there are no results dealing with the independence of the output bits. The well-known von Neumann corrector has an inefficient compression rate and the length of output bits is nondeterministic. Since the heavy cryptographic algorithms are used in the NIST’s conditioning component to reduce the bias of input bits, it is not appropriate in a lightweight environment. Thus we have concentrated on the linear code corrector and obtained the lightweight BCH code corrector with measurable dependence among the output bits as well as the bias. Moreover, we provide some simulations to examine our results.

A Dynamic Equilibrium Algorithm to Enhance Randomness in TRNG

2018 ◽  
Vol 27 (06) ◽  
pp. 1850095
Author(s):  
Chenyang Guo ◽  
Yujie Zhou
Keyword(s):  
Random Number ◽  
Dynamic Equilibrium ◽  
Random Number Generator ◽  
Pass Rate ◽  
Compression Rate ◽  
Number Generator ◽  
Post Processing ◽  
Processing Module ◽  
Great Solution ◽  
Software And Hardware

In this paper, a new method is proposed for randomness enhancement. The approach is called the dynamic equilibrium algorithm (DEA). It is used to solve the problems existing in the true random number generator (TRNG). First, the advantages and defects of LFSR as a post-processing module are discussed. When sampling 1000 groups of data, only 517 groups can pass all 15 tests in SP800-22 with a pass rate of 0.981. DEA is actually a great solution to this problem. The essence of DEA is to guarantee the approximately uniform distribution of the overlapping template to improve the bit-entropy by the compression of the data. This method is easy to implement in both software and hardware. The pass rate increases more than 40% with a low compression rate.

scholarly journals Design of Pseudo Random Number Generator using Linear Feedback Shift Register

2019 ◽  
Vol 9 (2) ◽  
pp. 1956-1965 ◽  
Keyword(s):  
Information Technology ◽  
Random Number ◽  
Random Number Generator ◽  
Shift Register ◽  
Linear Feedback Shift Register ◽  
Linear Feedback ◽  
Number Generator ◽  
Cryptographic Algorithms ◽  
Feedback Shift Register ◽  
Pseudo Random Number Generator

Nowadays security has become a great concern in the field of computer science and information technology. In order to protect data from unintended users and to achieve a desirable level of security, several cryptographic algorithms based on various technology have been proposed. Linear Feedback Shift Register (LFSR) may play an important role in the design of such cryptographic algorithms. LFSR based cryptographic algorithms are often lightweight in nature and are more suitable for resource constraining devices. In this paper we present a detailed analysis of LFSR and design of LFSR to implement cryptographic algorithms.

scholarly journals A New Statistical Test for PRNG Based on the Attendance’s Law

2021 ◽  
pp. 37-46
Author(s):  
Babacar Alasane Ndaw ◽  
Ousmane Ndiaye ◽  
Mamadou Sanghar´e ◽  
Cheikh Thi´ecoumba Gueye
Keyword(s):  
Random Number ◽  
Statistical Tests ◽  
Random Number Generator ◽  
Deterministic Algorithm ◽  
Statistical Test ◽  
The Other ◽  
Cryptographic Primitives ◽  
Random Number Generators ◽  
Other Hand ◽  
The One

One family of the cryptographic primitives is random Number Generators (RNG) which have several applications in cryptography such that password generation, nonce generation, Initialisation vector for Stream Cipher, keystream. Recently they are also used to randomise encryption and signature schemes. A pseudo-random number generator (PRNG) or a pseudo-random bit generator (PRBG) is a deterministic algorithm that produces numbers whose distribution is on the one hand indistinguishable from uniform ie. that the probabilities of appearance of the different symbols are equal and that these appearances are all independent. On the other hand, the next output of a PRNG must be unpredictable from all its previous outputs. Indeed, A set of statistical tests for randomness has been proposed in the literature and by NIST to evaluate the security of random(pseudo) bit or block. Unfortunately there are non-random binary streams that pass these standardized tests. In this pap er, as outcome, we intro duce on the one hand a new statistical test in a static contextcalled attendance’s law and on the other hand a distinguisher based on this new attendance’s law.    

scholarly journals Deciphering an Image Cipher Based on Mixed Transformed Logistic Maps

2015 ◽  
Vol 25 (13) ◽  
pp. 1550188 ◽  
Author(s):  
Yuansheng Liu ◽  
Hua Fan ◽  
Eric Yong Xie ◽  
Ge Cheng ◽  
Chengqing Li
Keyword(s):  
Computational Complexity ◽  
Random Number ◽  
Logistic Map ◽  
Random Number Generator ◽  
Number Generator ◽  
John Von Neumann ◽  
Von Neumann ◽  
Image Cipher ◽  
Encryption Schemes ◽  
Plain Image

Since John von Neumann suggested utilizing Logistic map as a random number generator in 1947, a great number of encryption schemes based on Logistic map and/or its variants have been proposed. This paper re-evaluates the security of an image cipher based on transformed logistic maps and proves that the image cipher can be deciphered efficiently under two different conditions: (1) two pairs of known plain-images and the corresponding cipher-images with computational complexity of [Formula: see text]; (2) two pairs of chosen plain-images and the corresponding cipher-images with computational complexity of [Formula: see text], where [Formula: see text] is the number of pixels in the plain-image. In contrast, the required condition in the previous deciphering method is 87 pairs of chosen plain-images and the corresponding cipher-images with computational complexity of [Formula: see text]. In addition, three other security flaws existing in most Logistic-map-based ciphers are also reported.

scholarly journals A quantum random number generator certified by value indefiniteness

2014 ◽  
Vol 24 (3) ◽  
Author(s):  
ALASTAIR A. ABBOTT ◽  
CRISTIAN S. CALUDE ◽  
KARL SVOZIL
Keyword(s):  
Random Number ◽  
Random Number Generator ◽  
Physical Principle ◽  
Mathematical Form ◽  
Number Generator ◽  
Open Problems ◽  
Efficient Procedure ◽  
Von Neumann ◽  
Quantum Bit ◽  
Temporal Correlations

In this paper we propose a quantum random number generator (QRNG) that uses an entangled photon pair in a Bell singlet state and is certified explicitly by value indefiniteness. While ‘true randomness’ is a mathematical impossibility, the certification by value indefiniteness ensures that the quantum random bits are incomputable in the strongest sense. This is the first QRNG setup in which a physical principle (Kochen–Specker value indefiniteness) guarantees that no single quantum bit that is produced can be classically computed (reproduced and validated), which is the mathematical form of bitwise physical unpredictability.We discuss the effects of various experimental imperfections in detail: in particular, those related to detector efficiencies, context alignment and temporal correlations between bits. The analysis is very relevant for the construction of any QRNG based on beam-splitters. By measuring the two entangled photons in maximally misaligned contexts and using the fact that two bitstrings, rather than just one, are obtained, more efficient and robust unbiasing techniques can be applied. We propose a robust and efficient procedure based onXORing the bitstrings together – essentially using one as a one-time-pad for the other – to extract random bits in the presence of experimental imperfections, as well as a more efficient modification of the von Neumann procedure for the same task. We also discuss some open problems.

scholarly journals Middle Square Method Analysis of Number Pseudorandom Process

2020 ◽  
Vol 4 (2) ◽  
pp. 35
Author(s):  
Arif Budiman ◽  
Efori Bulolo ◽  
Imam Saputra
Keyword(s):  
Data Collection ◽  
Random Number ◽  
Random Number Generator ◽  
Random Numbers ◽  
Number Generator ◽  
Cryptographic Algorithms ◽  
Mathematical Formulas ◽  
Method Analysis

Random numbers can be generated from a calculation of mathematical formulas. Such random numbers are often referred to as pseudo random numbers, random numbers are used for various algorithms, especially cryptographic algorithms such as AES, RSA, IDEA, GOST that require the use of Middle-Square Method random numbers which is very useful for adding research references to algorithms concerning random number generator and better understand how random numbers are generated using the Middle-Square Method algorithm. Both data collection and report making as for the objectives achieved in the form of understanding random numbers and knowing the algorithm process, compile a program designed to be used as an alternative to random numbers for various purposes, especially in cryptographic algorithms.

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