scholarly journals Introduction to Stochastic Computing using a Remote Lab with Reconfigurable Logic

2016 ◽  
Vol 12 (04) ◽  
pp. 23
Author(s):  
Jorge Lobo
Keyword(s):  
Random Number ◽  
Random Number Generation ◽  
Linear Feedback ◽  
Short Paper ◽  
Integration Time ◽  
Random Numbers ◽  
Reconfigurable Logic ◽  
Linear Feedback Shift Registers ◽  
Stochastic Computing ◽  
Remote Lab

This short paper introduces the basic concepts of Stochastic Computing (SC), and presents additions to a remote lab with reconfigurable logic to allow testing SC circuits. Recently, SC has been revisited and evaluated as a possible way of performing approximate probabilistic computations for artificial perception systems. New modules allow the generation of pseudo-random numbers, given a seed key and using linear feedback shift registers, but also having true random number generation using ring oscillators and embedded PLLs. Stochastic computing allows a tradeoff between resource usage and precision, allowing very simple circuits to perform computations, at the expense of a longer integration time to have reasonable results. We provide the basic stochastic computing modules, so that any user can use them to build a stochastic computing circuit and go beyond software simulations, providing a remote hardware device to test real circuits at high clock speeds.

scholarly journals Area-Efficient Error Detection Structure for Linear Feedback Shift Registers

Electronics ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 195
Author(s):  
Hwasoo Shin ◽  
Soyeon Choi ◽  
Jiwoon Park ◽  
Byeong Yong Kong ◽  
Hoyoung Yoo
Keyword(s):  
Error Detection ◽  
Random Number ◽  
Random Number Generation ◽  
Linear Feedback ◽  
Error Correction Codes ◽  
Parity Check ◽  
Linear Feedback Shift Registers ◽  
Encryption Algorithms ◽  
Feedback Shift Register ◽  
Additional Area

This paper presents a novel error detection linear feedback shift register (ED-LFSR), which can be used to realize error detection with a small hardware overhead for various applications such as error-correction codes, encryption algorithms and pseudo-random number generation. Although the traditional redundancy methods allow the incorporation of the error detection/correction capability in the original LFSRs, they suffer from a considerable amount of hardware overheads. The proposed ED-LFSR alleviates such problems by employing the parity check technique. The experimental results indicate that the proposed ED-LFSR requires an additional area of only 31.1% compared to that required by the conventional LFSR and it saves 39.1% and 31.9% of the resources compared to the corresponding utilization of the hardware and time redundancy methods.

scholarly journals A Hardware Pseudo-Random Number Generator Using Stochastic Computing and Logistic Map

Micromachines ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 31
Author(s):  
Junxiu Liu ◽  
Zhewei Liang ◽  
Yuling Luo ◽  
Lvchen Cao ◽  
Shunsheng Zhang ◽  
...  
Keyword(s):  
Random Number ◽  
Chaotic Map ◽  
Logistic Map ◽  
Random Number Generator ◽  
Alternative Methods ◽  
Random Numbers ◽  
Number Generator ◽  
Stochastic Computing ◽  
Pseudo Random Number ◽  
Pseudo Random Number Generator

Recent research showed that the chaotic maps are considered as alternative methods for generating pseudo-random numbers, and various approaches have been proposed for the corresponding hardware implementations. In this work, an efficient hardware pseudo-random number generator (PRNG) is proposed, where the one-dimensional logistic map is optimised by using the perturbation operation which effectively reduces the degradation of digital chaos. By employing stochastic computing, a hardware PRNG is designed with relatively low hardware utilisation. The proposed hardware PRNG is implemented by using a Field Programmable Gate Array device. Results show that the chaotic map achieves good security performance by using the perturbation operations and the generated pseudo-random numbers pass the TestU01 test and the NIST SP 800-22 test. Most importantly, it also saves 89% of hardware resources compared to conventional approaches.

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.

LFSR-Keyed MUX for Random Number Generation in Nano Communication Using QCA

2020 ◽  
pp. 70-83
Author(s):  
Padmapriya Praveenkumar ◽  
Santhiya Devi R. ◽  
Amirtharajan Rengarajan ◽  
John Bosco Balaguru Rayappan
Keyword(s):  
Cellular Automata ◽  
Random Number ◽  
Random Number Generator ◽  
Random Number Generation ◽  
Linear Feedback ◽  
Innovative Technology ◽  
Minimal Size ◽  
Quantum Cellular Automata ◽  
Technology Roadmap ◽  
Feedback Shift Register

Nano industries have been successful trendsetters for the past 30 years, in escalating the speed and dropping the power necessities of nanoelectronic devices. According to Moore's law and the assessment created by the international technology roadmap for semiconductors, beyond 2020, there will be considerable restrictions in manufacturing IC's based on CMOS technologies. As a result, the next prototype to get over these effects is quantum-dot cellular automata (QCA). In this chapter, an efficient quantum cellular automata (QCA) based random number generator (RNG) is proposed. QCA is an innovative technology in the nano regime which guarantees large device density, less power dissipation, and minimal size as compared to the various CMOS technologies. With the aim to maximise the randomness in the proposed nano communication, a linear feedback shift register (LFSR) keyed multiplexer with ring oscillators is developed. The developed RNG is simulated using a quantum cellular automata (QCA) simulator tool.

scholarly journals True Random Number Generation from Bioelectrical and Physical Signals

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Seda Arslan Tuncer ◽  
Turgay Kaya
Keyword(s):  
Blood Volume ◽  
Random Number ◽  
Logistic Map ◽  
Random Number Generation ◽  
Statistical Properties ◽  
Random Numbers ◽  
Number Generation ◽  
Skin Response ◽  
Volume Pulse ◽  
Blood Volume Pulse

It is possible to generate personally identifiable random numbers to be used in some particular applications, such as authentication and key generation. This study presents the true random number generation from bioelectrical signals like EEG, EMG, and EOG and physical signals, such as blood volume pulse, GSR (Galvanic Skin Response), and respiration. The signals used in the random number generation were taken from BNCIHORIZON2020 databases. Random number generation was performed from fifteen different signals (four from EEG, EMG, and EOG and one from respiration, GSR, and blood volume pulse datasets). For this purpose, each signal was first normalized and then sampled. The sampling was achieved by using a nonperiodic and chaotic logistic map. Then, XOR postprocessing was applied to improve the statistical properties of the sampled numbers. NIST SP 800-22 was used to observe the statistical properties of the numbers obtained, the scale index was used to determine the degree of nonperiodicity, and the autocorrelation tests were used to monitor the 0-1 variation of numbers. The numbers produced from bioelectrical and physical signals were successful in all tests. As a result, it has been shown that it is possible to generate personally identifiable real random numbers from both bioelectrical and physical signals.

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.

A Low-Cost Highly Reliable Spintronic True Random Number Generator Circuit for Secure Cryptography

SPIN ◽  
2019 ◽  
Vol 10 (01) ◽  
pp. 2050003 ◽  
Author(s):  
Iman Alibeigi ◽  
Abdolah Amirany ◽  
Ramin Rajaei ◽  
Mahmoud Tabandeh ◽  
Saeed Bagheri Shouraki
Keyword(s):  
High Speed ◽  
High Performance ◽  
Random Number ◽  
Low Cost ◽  
Random Number Generator ◽  
Magnetic Tunnel Junction ◽  
Random Number Generation ◽  
Cmos Technology ◽  
Random Numbers ◽  
Number Generation

Generation of random numbers is one of the most important steps in cryptographic algorithms. High endurance, high performance and low energy consumption are the attractive features offered by the Magnetic Tunnel Junction (MTJ) devices. Therefore, they have been considered as one of the promising candidates for next-generation digital integrated circuits. In this paper, a new circuit design for true random number generation using MTJs is proposed. Our proposed circuit offers a high speed, low power and a truly random number generation. In our design, we employed two MTJs that are configured in special states. Generated random bit at the output of the proposed circuit is returned to the write circuit to be written in the relevant cell for the next random generation. In a random bitstream, all bits must have the same chance of being “0”or “1”. We have proposed a new XOR-based method in this paper to resolve this issue in multiple random generators that produce truly random numbers with a different number of ones and zeros in the output stream. The simulation results using a 45[Formula: see text]nm CMOS technology with a special model of MTJ validated the advantages offered by the proposed circuit.

scholarly journals Sensor-Seeded Cryptographically Secure Random Number Generation

2019 ◽  
Vol 8 (3) ◽  
pp. 1854-1857
Keyword(s):  
Random Number ◽  
Random Sequence ◽  
Random Number Generation ◽  
Sensor Data ◽  
Random Numbers ◽  
Pseudorandom Number Generator ◽  
Random Number Generators ◽  
Secret Keys ◽  
Initialization Vector ◽  
Entropy Source

Random numbers are essential to generate secret keys, initialization vector, one-time pads, sequence number for packets in network and many other applications. Though there are many Pseudo Random Number Generators available they are not suitable for highly secure applications that require high quality randomness. This paper proposes a cryptographically secure pseudorandom number generator with its entropy source from sensor housed on mobile devices. The sensor data are processed in 3-step approach to generate random sequence which in turn fed to Advanced Encryption Standard algorithm as random key to generate cryptographically secure random numbers.

scholarly journals Twister Generator of Stochastic Planes

2019 ◽  
pp. 27-45
Author(s):  
A.F. Deon ◽  
V.A. Onuchin ◽  
Yu.A. Menyaev
Keyword(s):  
Random Number ◽  
Random Access ◽  
Random Number Generation ◽  
Random Numbers ◽  
Access Memory ◽  
Number Generation ◽  
Novel Approach ◽  
Pseudorandom Number Generation ◽  
Sequence Parameters ◽  
Uniform Random Numbers

Various pseudorandom number generation algorithms may be used to create a discrete stochastic plane. If a Cartesian completeness property is required of the plane, it must be uniform. The point is, employing the concept of uncontrolled random number generation may yield low-quality results, since original sequences may omit random numbers or not be sufficiently uniform. We present a novel approach for generating stochastic Cartesian planes according to the model of complete twister sequences featuring uniform random numbers without omissions or repetitions. Simulation results confirm that the random planes obtained are indeed perfectly uniform. Moreover, recombining the original complete uniform sequence parameters allows the number of planes created to be significantly increased without using any extra random access memory.

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