scholarly journals RRAM Random Number Generator Based on Train of Pulses

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1831
Author(s):  
Binbin Yang ◽  
Daniel Arumí ◽  
Salvador Manich ◽  
Álvaro Gómez-Pau ◽  
Rosa Rodríguez-Montañés ◽  
...  

In this paper, the modulation of the conductance levels of resistive random access memory (RRAM) devices is used for the generation of random numbers by applying a train of RESET pulses. The influence of the pulse amplitude and width on the device resistance is also analyzed. For each pulse characteristic, the number of pulses required to drive the device to a particular resistance threshold is variable, and it is exploited to extract random numbers. Based on this behavior, a random number generator (RNG) circuit is proposed. To assess the performance of the circuit, the National Institute of Standards and Technology (NIST) randomness tests are applied to evaluate the randomness of the bitstreams obtained. The experimental results show that four random bits are simultaneously obtained, passing all the applied tests without the need for post-processing. The presented method provides a new strategy to generate random numbers based on RRAMs for hardware security applications.

2012 ◽  
Vol 33 (8) ◽  
pp. 1108-1110 ◽  
Author(s):  
Chien-Yuan Huang ◽  
Wen Chao Shen ◽  
Yuan-Heng Tseng ◽  
Ya-Chin King ◽  
Chrong-Jung Lin

SPIN ◽  
2019 ◽  
Vol 09 (03) ◽  
pp. 1940009
Author(s):  
Akio Fukushima ◽  
Kay Yakushiji ◽  
Hitoshi Kubota ◽  
Hiroshi Imamura ◽  
Shinji Yuasa

We have developed a random-number-generator (RNG) named “spin dice,” which employs the stochastic nature of spin-torque switching (STS) in a magnetic tunnel junction. The principle of the idea is that the switching probability first tuned around 0.5 is varied linearly with the applied current. After that, the switching results are converted into binary random numbers. We fabricated several types of “spin dice” by combining magnetic tunnel junctions and single-board microcomputer, and achieved generation speed of random numbers up to several hundred kbit/sec. Because STS is scalable and magnetic tunnel junctions have compatibility to semiconductor fabrication process, “spin dice” can be considered as a promising candidate for truly random-number-generator (TRNG) for security applications.


Micromachines ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 31
Author(s):  
Junxiu Liu ◽  
Zhewei Liang ◽  
Yuling Luo ◽  
Lvchen Cao ◽  
Shunsheng Zhang ◽  
...  

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.


2020 ◽  
Author(s):  
Gwangmin Kim ◽  
Jae Hyun In ◽  
Hakseung Rhee ◽  
Woojoon Park ◽  
Hanchan Song ◽  
...  

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.


Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1869 ◽  
Author(s):  
Luca Baldanzi ◽  
Luca Crocetti ◽  
Francesco Falaschi ◽  
Matteo Bertolucci ◽  
Jacopo Belli ◽  
...  

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.


2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Wang Xingyuan ◽  
Qin Xue ◽  
Teng Lin

We propose a novel true random number generator using mouse movement and a one-dimensional chaotic map. We utilize thex-coordinate of the mouse movement to be the length of an iteration segment of our TRNs and they-coordinate to be the initial value of this iteration segment. And, when it iterates, we perturb the parameter with the real value produced by the TRNG itself. And we find that the TRNG we proposed conquers several flaws of some former mouse-based TRNGs. At last we take experiments and test the randomness of our algorithm with the NIST statistical test suite; results illustrate that our TRNG is suitable to produce true random numbers (TRNs) on universal personal computers (PCs).


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