Low-Power True Random Number Generator Based on Randomly Distributed Carbon Nanotube Networks

Abstract

Although the intrinsic variability in nanoelectronic devices has been a major obstacle and has prevented mass production, this natural stochasticity can be an asset in hardware security applications. Herein, we demonstrate a true random number generator (TRNG) based on stochastic carrier trapping/detrapping processes in randomly distributed carbon nanotube networks. The bitstreams collected from the TRNG passed all the National Institute of Standards and Technology randomness tests without post-processing. The random bit generated in this study is sufficient for encryption applications, particularly those related to the Internet of Things and edge computing, which require significantly lower power consumption.INDEX TERMS carbon nanotube network, random number generator, stochastic carrier trapping

A Peripheral-Free True Random Number Generator Based on Integrated Circuits Enabled by Atomically Thin Two-Dimensional Materials

“…Additionally, CMOS-derived TRNGs are known to suffer from low entropy and require peripherals to eliminate device mismatches. Recent years have also witnessed the development of stochastic switching mechanisms in memristors, , random spin flips in magnetic devices, polarization switching in ferroelectric materials, and stochastic charge trapping in nanoscale devices , as high entropy sources for generating TRNGs. However, integrating peripherals such as comparators, logic gates, registers, and counters increases their energy and area overheads, posing a challenge in enabling a peripheral-free TRNG for low-power security solutions in emerging IoT devices.…”

A High-Quality Entropy Source Using van der Waals Heterojunction for True Random Number Generation

“…Quantum TRNGs rely on the probabilistic nature of the quantum events for randomness, while classical TRNGs such as TRNGs based on classical chaos rely on the indeterminism caused by finite measurement accuracy and the high sensitivity to initial conditions as the source of randomness. Utilizing these processes, TRNGs based on chaotic lasers, multimodal ring oscillators, random Raman fiber lasers, memristors, − amplified spontaneous emission, photon arrival time measurements, superparamagnetic tunnel junctions, carbon nanotube transistors, etc ., have been demonstrated recently. Together with the quality of randomness produced, the compactness and scalability of these technologies also play a crucial role in determining the real-life applicability of these physical processes as TRNGs.…”

“…Owing to the criticality of applications that employ TRNGs and the diversity of physical processes used, a rigorous methodology to characterize the quality of randomness extracted by a TRNG is of utmost significance. A battery of tests as recommended in the National Institute of Standards and Technology (NIST) SP 800-22 statistical test suite are typically employed in the literature to assess the randomness of the generated output bits. ,,− We wish to emphasize that the NIST SP 800-22 battery of tests does not scrutinize the true randomness but instead analyzes the output of a true/pseudorandom source for features desirable for applications in cryptography. On the other hand, entropy has been in use in various fields of study as a measure to quantify the degree of uncertainty present in a system and was introduced to information theory by Shannon in his seminal paper .…”

A High-Quality Entropy Source Using van der Waals Heterojunction for True Random Number Generation

“…Quantum TRNGs rely on the probabilistic nature of the quantum events for randomness, while classical TRNGs such as TRNGs based on classical chaos rely on the indeterminism caused by finite measurement accuracy and the high sensitivity to initial conditions as the source of randomness. Utilizing these processes, TRNGs based on chaotic lasers, 3 multi-modal ring oscillators, 4 random Raman fiber lasers, 5 memristors, [6][7][8] amplified spontaneous emission, 9 photon arrival time measurements, 10 superparamagnetic tunnel junctions, 11 carbon nanotube transistors, 12 etc. have been demonstrated recently.…”

“…A battery of tests as recommended in the National Institute of Standards and Technology (NIST) SP 800-22 statistical test suite 14 are typically employed in literature to assess the randomness of the generated output bits. 5,6,[9][10][11][12][13] We wish to emphasize that the NIST SP 800-22 battery of tests does not scrutinize the true randomness but instead analyzes the output of a true/pseudo-random source for features desirable for applications in cryptography. On the other hand, entropy has been in use in various fields of study as a measure to quantify the degree of uncertainty present in a system and was introduced to information theory by Shannon in his seminal paper.…”