scholarly journals Random Number Generator with Long-Range Dependence and Multifractal Behavior Based on Memristor

Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1607 ◽  
Author(s):  
María Téllez ◽  
Johan Mejía ◽  
Hans López ◽  
Cesar Hernández
Keyword(s):  
Long Range ◽  
Random Number ◽  
System Modeling ◽  
Random Number Generator ◽  
Random Number Generation ◽  
Long Range Dependence ◽  
Hurst Parameter ◽  
Number Generator ◽  
Behavior Based ◽  
Multifractal Behavior

Random number generators are used in areas such as encryption and system modeling, where some of these exhibit fractal behaviors. For this reason, it is interesting to make use of the memristor characteristics for the random number generation. Accordingly, the objective of this article is to evaluate the performance of a chaotic memristive system as a random number generator with fractal behavior and long-range dependence. To achieve the above, modeling memristor and its corresponding chaotic systems is performed, from which a random number generator is constructed. Subsequently, the Hurst parameter for the detection of long-range dependence is estimated and a fractal analysis of the synthesized data is performed. Finally, a comparison between the model proposed in the research and the β-MWM algorithm is made. The results obtained show that the data synthesized from the proposed generator have a variable Hurst parameter and both monofractal and multifractal behavior. The main contribution of this research is the proposal of a new model for the synthesis of traces with long-range dependence and fractal behavior based on the non-linearity of the memristor.

scholarly journals True Random Number Generator Based on Fibonacci-Galois Ring Oscillators for FPGA

2021 ◽  
Vol 11 (8) ◽  
pp. 3330
Author(s):  
Pietro Nannipieri ◽  
Stefano Di Matteo ◽  
Luca Baldanzi ◽  
Luca Crocetti ◽  
Jacopo Belli ◽  
...  
Keyword(s):  
Field Programmable Gate Array ◽  
Random Number ◽  
Random Number Generator ◽  
Random Number Generation ◽  
Galois Ring ◽  
Number Generator ◽  
True Random Number Generator ◽  
Number Generation ◽  
Field Programmable ◽  
Gate Array

Random numbers are widely employed in cryptography and security applications. If the generation process is weak, the whole chain of security can be compromised: these weaknesses could be exploited by an attacker to retrieve the information, breaking even the most robust implementation of a cipher. Due to their intrinsic close relationship with analogue parameters of the circuit, True Random Number Generators are usually tailored on specific silicon technology and are not easily scalable on programmable hardware, without affecting their entropy. On the other hand, programmable hardware and programmable System on Chip are gaining large adoption rate, also in security critical application, where high quality random number generation is mandatory. The work presented herein describes the design and the validation of a digital True Random Number Generator for cryptographically secure applications on Field Programmable Gate Array. After a preliminary study of literature and standards specifying requirements for random number generation, the design flow is illustrated, from specifications definition to the synthesis phase. Several solutions have been studied to assess their performances on a Field Programmable Gate Array device, with the aim to select the highest performance architecture. The proposed designs have been tested and validated, employing official test suites released by NIST standardization body, assessing the independence from the place and route and the randomness degree of the generated output. An architecture derived from the Fibonacci-Galois Ring Oscillator has been selected and synthesized on Intel Stratix IV, supporting throughput up to 400 Mbps. The achieved entropy in the best configuration is greater than 0.995.

scholarly journals Self-clocking fast and variation tolerant true random number generator based on a stochastic mott memristor

2020 ◽  
Author(s):  
Gwangmin Kim ◽  
Jae Hyun In ◽  
Hakseung Rhee ◽  
Woojoon Park ◽  
Hanchan Song ◽  
...  
Keyword(s):  
Random Number ◽  
Random Number Generator ◽  
Random Number Generation ◽  
Harsh Environments ◽  
Random Numbers ◽  
Number Generator ◽  
High Tolerance ◽  
Stochastic Oscillation ◽  
Advanced Method ◽  
Intrinsic Stochasticity

Abstract The intrinsic stochasticity of the memristor can be used to generate true random numbers, essential for non-decryptable hardware-based security devices. Here we propose a novel and advanced method to generate true random numbers utilizing the stochastic oscillation behavior of a NbOx mott memristor, exhibiting self-clocking, fast and variation tolerant characteristics. The random number generation rate of the device can be at least 40 kbs-1, which is the fastest record compared with previous volatile memristor-based TRNG devices. Also, its dimensionless operating principle provides high tolerance against both ambient temperature variation and device-to-device variation, enabling robust security hardware applicable in harsh environments.

Pseudo-random number generation using a 3-state cellular automaton

2017 ◽  
Vol 28 (06) ◽  
pp. 1750078 ◽  
Author(s):  
Kamalika Bhattacharjee ◽  
Dipanjyoti Paul ◽  
Sukanta Das
Keyword(s):  
Cellular Automaton ◽  
Random Number ◽  
Random Number Generator ◽  
Random Number Generation ◽  
Number Generator ◽  
Number Generation ◽  
Pseudo Random Number ◽  
Empirical Tests ◽  
Pseudo Random Number Generator

This paper investigates the potentiality of pseudo-random number generation of a 3-neighborhood 3-state cellular automaton (CA) under periodic boundary condition. Theoretical and empirical tests are performed on the numbers, generated by the CA, to observe the quality of it as pseudo-random number generator (PRNG). We analyze the strength and weakness of the proposed PRNG and conclude that the selected CA is a good random number generator.

SRAM Based Random Number Generator for Non-Repeating Pattern Generation

2014 ◽  
Vol 573 ◽  
pp. 181-186 ◽  
Author(s):  
G.P. Ramesh ◽  
A. Rajan
Keyword(s):  
Random Number ◽  
Statistical Tests ◽  
Random Number Generator ◽  
Random Number Generation ◽  
Pattern Generation ◽  
Storage Device ◽  
Number Generator ◽  
Random Number Generators ◽  
Field Programmable ◽  
The Look

—Field-programmable gate array (FPGA) optimized random number generators (RNGs) are more resource-efficient than software-optimized RNGs because they can take advantage of bitwise operations and FPGA-specific features. A random number generator (RNG) is a computational or physical device designed to generate a sequence of numbers or symbols that lack any pattern, i.e. appear random. The many applications of randomness have led to the development of several different methods for generating random data. Several computational methods for random number generation exist, but often fall short of the goal of true randomness though they may meet, with varying success, some of the statistical tests for randomness intended to measure how unpredictable their results are (that is, to what degree their patterns are discernible).LUT-SR Family of Uniform Random Number Generators are able to handle randomness only based on seeds that is loaded in the look up table. To make random generation efficient, we propose new approach based on SRAM storage device.Keywords: RNG, LFSR, SRAM

scholarly journals Cryptographically Secure Pseudo-Random Number Generator IP-Core Based on SHA2 Algorithm

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1869 ◽  
Author(s):  
Luca Baldanzi ◽  
Luca Crocetti ◽  
Francesco Falaschi ◽  
Matteo Bertolucci ◽  
Jacopo Belli ◽  
...  
Keyword(s):  
High Performance ◽  
Random Number ◽  
Random Number Generator ◽  
Random Number Generation ◽  
Random Numbers ◽  
Generation Process ◽  
Number Generator ◽  
Ip Core ◽  
Pseudo Random Number ◽  
Pseudo Random Number Generator

In the context of growing the adoption of advanced sensors and systems for active vehicle safety and driver assistance, an increasingly important issue is the security of the information exchanged between the different sub-systems of the vehicle. Random number generation is crucial in modern encryption and security applications as it is a critical task from the point of view of the robustness of the security chain. Random numbers are in fact used to generate the encryption keys to be used for ciphers. Consequently, any weakness in the key generation process can potentially leak information that can be used to breach even the strongest cipher. This paper presents the architecture of a high performance Random Number Generator (RNG) IP-core, in particular a Cryptographically Secure Pseudo-Random Number Generator (CSPRNG) IP-core, a digital hardware accelerator for random numbers generation which can be employed for cryptographically secure applications. The specifications used to develop the proposed project were derived from dedicated literature and standards. Subsequently, specific architecture optimizations were studied to achieve better timing performance and very high throughput values. The IP-core has been validated thanks to the official NIST Statistical Test Suite, in order to evaluate the degree of randomness of the numbers generated in output. Finally the CSPRNG IP-core has been characterized on relevant Field Programmable Gate Array (FPGA) and ASIC standard-cell technologies.

scholarly journals A Novel Hypogenetic Chaotic Jerk System: Modeling, Circuit Implementation, and Its Application

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Jiancheng Liu ◽  
Karthikeyan Rajagopal ◽  
Tengfei Lei ◽  
Sezgin Kaçar ◽  
Burak Arıcıoğlu ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Electronic Circuit ◽  
Random Number ◽  
System Modeling ◽  
Random Number Generator ◽  
Superior Performance ◽  
Dynamical Analysis ◽  
Number Generator ◽  
Circuit Implementation ◽  
Jerk System

When revising the polarity and amplitude information in the feedback, a unique hypogenetic jerk system was obtained which has two controllers to switch the equilibria between stable and unstable. After providing some basic dynamical analysis, an electronic circuit was implemented, and the phase trajectory in the oscilloscope agrees with the numerical simulation. Further exploration shows that this unique chaotic system has superior performance as a random number generator or in voice encryption application.

scholarly journals Asymmetric Variate Generation via a Parameterless Dual Neural Learning Algorithm

2008 ◽  
Vol 2008 ◽  
pp. 1-8
Author(s):  
Simone Fiori
Keyword(s):  
Random Number ◽  
Learning Algorithm ◽  
Random Number Generator ◽  
Learning Rule ◽  
Random Number Generation ◽  
Neural System ◽  
New Method ◽  
Number Generator ◽  
Number Generation ◽  
Neural Learning

In a previous work (S. Fiori, 2006), we proposed a random number generator based on a tunable non-linear neural system, whose learning rule is designed on the basis of a cardinal equation from statistics and whose implementation is based on look-up tables (LUTs). The aim of the present manuscript is to improve the above-mentioned random number generation method by changing the learning principle, while retaining the efficient LUT-based implementation. The new method proposed here proves easier to implement and relaxes some previous limitations.

Maximal length cellular automata in GF(q) and pseudo-random number generation

2020 ◽  
Vol 31 (03) ◽  
pp. 2050037
Author(s):  
Sumit Adak ◽  
Kamalika Bhattacharjee ◽  
Sukanta Das
Keyword(s):  
Cellular Automata ◽  
Random Number ◽  
Random Number Generator ◽  
Random Number Generation ◽  
Maximal Length ◽  
Number Generator ◽  
Greedy Strategy ◽  
Pseudo Random Number ◽  
Pseudo Random Number Generator

This work explores the randomness quality of maximal length cellular automata (CAs) in GF([Formula: see text]), where [Formula: see text]. A greedy strategy is chosen to select the candidate CAs which satisfy unpredictability criterion essential for a good pseudo-random number generator (PRNG). Then, performance of these CAs as PRNGs is empirically analyzed by using Diehard battery of tests. It is observed that, up to GF(11), increase in [Formula: see text] improves randomness quality of the CAs, but after that, it saturates. Finally, we propose an implementable design of a good PRNG based on a 13-cell maximal length cellular automaton over GF(11) which can compete with the existing well-known PRNGs.

scholarly journals Homodyne-based quantum random number generator at 2.9 Gbps secure against quantum side-information

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Tobias Gehring ◽  
Cosmo Lupo ◽  
Arne Kordts ◽  
Dino Solar Nikolic ◽  
Nitin Jain ◽  
...  
Keyword(s):  
Random Number ◽  
Side Information ◽  
Random Number Generator ◽  
Security Analysis ◽  
Random Number Generation ◽  
Vacuum State ◽  
Number Generator ◽  
Experimental Realization ◽  
Security Proof ◽  
Quantum Side Information

AbstractQuantum random number generators promise perfectly unpredictable random numbers. A popular approach to quantum random number generation is homodyne measurements of the vacuum state, the ground state of the electro-magnetic field. Here we experimentally implement such a quantum random number generator, and derive a security proof that considers quantum side-information instead of classical side-information only. Based on the assumptions of Gaussianity and stationarity of noise processes, our security analysis furthermore includes correlations between consecutive measurement outcomes due to finite detection bandwidth, as well as analog-to-digital converter imperfections. We characterize our experimental realization by bounding measured parameters of the stochastic model determining the min-entropy of the system’s measurement outcomes, and we demonstrate a real-time generation rate of 2.9 Gbit/s. Our generator follows a trusted, device-dependent, approach. By treating side-information quantum mechanically an important restriction on adversaries is removed, which usually was reserved to semi-device-independent and device-independent schemes.

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