Radiotekhnika

Methods and means for analysing, evaluating and comparing properties of random sequences and random numbers

D.Yu. Holubnychiy, Serhii Kandii, Maryna V. Yesina, D.Yu. Gorbenko

Published Mar 20, 2024• 1 citation

Abstract

Methods and means for analysing, assessing and comparing properties of random sequences and random numbers are considered in the work. The article also discusses such aspects as mathematical modeling of random processes, statistical methods for estimating distribution parameters, comparative analysis of the properties of random variables. To date, random sequences (RS) and random numbers (RN), produced by physically real (PT RNG) and non-physically real (NPT RNG) generators, are widely used in practice, they essentially legislate key generation mechanisms in cryptographic systems. Depending on the cryptographic transformations, they are used to generate long-term keys and session keys of symmetric cryptographic transformations, long-term asymmetric key pairs and session key pairs, general parameters of cryptographic transformations and cryptographic protocols, specific one-time values (nonces), challenges (challenges), blinding and masking values, etc. Among the set of requirements for such generators is the provision of the maximum possible value of the initial entropy in a number of, and possibly most, cryptographic applications. The analysis of international and national legal documents regarding the requirements for PT RNG and NPT RNG sources and, accordingly, generators, carried out in the work showed that they, taking into account the significant challenges associated with expanding the possibilities of cryptanalysis based on application, in addition to classical, quantum and side channel attacks should be significantly improved and evaluated using complex methods using a system of unconditional criteria. The purpose of this article is to substantiate, develop and confirm experimentally the correct application of RS and RN generation algorithms based on PTRNG and NPTRNG, including in the application of classical and quantum microelectronics, as well as the development of recommendations for their use for generating keys and parameters for quantum stable methods and standards of cryptographic transformations.

DOI: 10.30837/rt.2024.1.216.02

Related papers

Entropy and Randomness: From Analogic to Quantum World

Emil Simion

This work is dedicated to the construction and evaluation of random number generators used in cryptography. The critical element on which the security of information is based is the cryptographic key (usually a binary sequence). In order to be resistant to brute force attacks it is necessary that it be made up of random variables with a certain degree of randomness and independence. Formally, this comes back to generate the cryptographic key through the systems which ensures a certain minimum level of entropy. The observer has access to a sample, of a certain size, and based on it he will estimate the minimum value of the entropy, in the situations in which the variables resulting from the measurement process are independent. In the situation where these variables are not independent, complex mathematical procedures also allow estimation of the minimum entropy. This article is a review of how mathematical entropy can be estimated and evaluated, of the construction mode (from technologies based on analogue procedures: thermal noise in a transistor to modern procedures: quantum devices), as well as to evaluate the security of binary sequence generators used for generating cryptographic keys or critical security parameters related to new technologies based on quantum principles. The techniques and methods used to generate binary random values as well as the methods of statistical and informational validation (Shannon entropy) are exemplified in this paper.

IEEE AccessJan 1, 202030 citations

IMPLEMENTATION AND EVALUATION OF A QUANTUM RANDOM NUMBER GENERATOR BASED ON ANU QRNG FOR CRYPTOGRAPHIC APPLICATION

Софія Парфило, Віталій Вікторович Коваль

Topicality. Reliable random number generation is one of the key requirements for modern cryptographic systems and cybersecurity applications. Traditional pseudo-random number generators are based on deterministic algorithms and may exhibit limited entropy and predictability, which can negatively affect information security. The subject of study in the article is methods of quantum random number generation and approaches to evaluating the quality of generated random sequences. The purpose of the article is to analyze modern methods of quantum random number generation, develop a software tool for obtaining quantum random numbers based on the ANU Quantum Random Number Generator service, perform statistical testing of the generated sequences, and analyze the obtained results. The following results were obtained. Modern quantum random number generation systems were analyzed and compared. A software tool was implemented in Python for automatic retrieval of quantum random numbers through the ANU QRNG API. The generated binary sequences were evaluated using Frequency Test and Block Frequency Test from the NIST SP 800-22 statistical test suite. The obtained p-values were 0.977181 and 0.200659 respectively, confirming successful completion of both tests. Additionally, visual analysis of the generated sequences revealed no noticeable patterns or repetitive structures. Conclusion. The obtained results confirm the high quality of quantum random sequences generated using ANU QRNG and demonstrate the applicability of the developed software tool for cryptographic and cybersecurity applications requiring high-quality randomness.

Terra securityJul 4, 20260 citations

РЕАЛІЗАЦІЯ ТА ОЦІНЮВАННЯ КВАНТОВОГО ГЕНЕРАТОРА ВИПАДКОВИХ ЧИСЕЛ НА ОСНОВІ ANU QRNG ДЛЯ КРИПТОГРАФІЧНИХ ЗАСТОСУВАНЬ

Софія Парфило, Віталій Коваль

The Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogyJul 4, 20260 citations

Kriptografik rastgele sayı üreteçleri için entropi tahmin yöntemleri ve sağlık testleri

Melis Aslan

Random numbers play a crucial role in cryptography since the security of cryptographic protocols relies on the assumption of the availability of uniformly distributed and unpredictable random numbers to generate secret keys, passwords, initialization vectors, nonces, salt, etc. True Random Number Generators (TRNGs) extract random numbers from physical processes (such as radioactive decay, thermal noise, and atmospheric noise) that are inherently unpredictable. However, real-world random number generators sometimes fail and produce outputs with low entropy, leading to security vulnerabilities. It is commonly observed that the TRNG outputs have statistical biases and dependencies that make them unsuitable to be directly used for cryptographic purposes. There are some standards and guidelines on generating and testing random numbers that are suitable for cryptographic applications. The National Institute of Standards and Technology (NIST) Special Publication (SP) 800-90 series provide guidelines and recommendations for generating random numbers for cryptographic applications and describes statistical randomness testing, estimating min-entropy with 10 black-box entropy estimation methods. In this thesis, we evaluate the effectiveness and limitations of the SP 800-90B methods by exploring the accuracy of these estimators using simulated random numbers with known entropy, investigating the correlation between entropy estimates, and studying the impacts of deterministic transformations on the estimators. To understand the unpredictability of the outputs, it is important to estimate their entropy accurately. The National Institute of Standards and Technology (NIST) Special Publication (SP) 800-90B specifies ten min-entropy estimators ranging from simple frequency-based estimators to more advanced approaches. Each estimator has specific assumptions, making them suitable for different types of sources. The minimum of these estimates is assumed to be the min-entropy of the TRNG. We propose a new entropy estimator (estimates min-entropy and also Shannon entropy) called index-value coincidence estimate that is suitable for outputs that might include some dependencies and we also provide some experimental results that demonstrate the effectiveness of the estimator. Additionally, TRNGs may be affected by outside conditions such as temperature, humidity, etc. Health tests are an integral part of the noise source of TRNG, defined to detect unexpected changes in the working process and dramatic changes in the amount of entropy generated by the noise source. Existing health test suites are examined, and a health test suite for cryptographic TRNGs is introduced by using random variables weight, run, runs of length 1 and overlapping templates. Some suggested parameters and experimental results are given.

Sep 25, 20240 citations

Analysis of entropy extraction efficiencies in random number generation systems

Chao Wang, Shuang Wang, Wei Chen +2 more

Random numbers (RNs) have applications in many areas: lottery games, gambling, computer simulation, and, most importantly, cryptography [N. Gisin et al., Rev. Mod. Phys. 74 (2002) 145]. In cryptography theory, the theoretical security of the system calls for high quality RNs. Therefore, developing methods for producing unpredictable RNs with adequate speed is an attractive topic. Early on, despite the lack of theoretical support, pseudo RNs generated by algorithmic methods performed well and satisfied reasonable statistical requirements. However, as implemented, those pseudorandom sequences were completely determined by mathematical formulas and initial seeds, which cannot introduce extra entropy or information. In these cases, “random” bits are generated that are not at all random. Physical random number generators (RNGs), which, in contrast to algorithmic methods, are based on unpredictable physical random phenomena, have attracted considerable research interest. However, the way that we extract random bits from those physical entropy sources has a large influence on the efficiency and performance of the system. In this manuscript, we will review and discuss several randomness extraction schemes that are based on radiation or photon arrival times. We analyze the robustness, post-processing requirements and, in particular, the extraction efficiency of those methods to aid in the construction of efficient, compact and robust physical RNG systems.

International Journal of Quantum InformationFeb 1, 20160 citations

Random number generator for cryptography

Ram Soorat, K. Madhuri, Ashok Vudayagiri

One key requirement for many cryptograhic schemes is the generation of random numbers.Sequences of random numbers are used at several stages of a standard cryptographic protocol.One simple example is a Vernam cipher, where a string of random numbers is added to message string to generate encrypted code.C = M ⊕ K.It has been mathematically shown that this simple scheme is unbreakable if key K is as long as M and is used only once.The security of a cryptosystem shall not be based on keeping the algorithm secret but solely on keeping the key secret.The security of a random number generator (RNG) is related to the difficulty of predicting its future sequence values from past values.The quality and unpredictability of secret data is critical to securing communication by modern cryptographic techniques.The generation of such data for cryptographic purposes typically requires an unpredictable physical source of random data.We studied a chaotic circuit which consisted of an inductor, capacitance, diode and thus used for the BB84 protocol.We have studied both pseudo random and true random number generators and evaluated them through various tests like frequency, correlation, NIST etc.

Nanosystems Physics Chemistry MathematicsOct 27, 20174 citations