Cryptographic transistor for true random number generator with low power consumption.

A true random number generator (TRNG) is suitable for generating secure keys and nonces. TRNGs implemented in IoT devices must be small in scale and have low power consumption. The random number sequence generated by TRNG needs to have high entropy immediately after startup and a stable state. In this paper, three types of ring oscillator type TRNGs, TERO-based, COSO-based, and STR-based TRNG, are implemented on Zynq-7010. When these TRNGs are implemented as a single entropy source, it is challenging to implement them because it is necessary to evaluate the layout and wiring for each FPGA. This paper proposes a TRNG configuration, which exclusively ORs the outputs of multiple entropy sources. We show that this configuration can reduce the implementing difficulty and realize high entropy. For the random number sequence evaluation, we use the statistical test of NIST SP800-90B and BSI AIS 20/31. In addition, the random number sequence immediately after the startup is also statistically evaluated. As a result, our proposed TRNGs generate high entropy random numbers and are easy to implement on FPGA when we implement TRNGs with eight single entropy sources for TERO-based TRNG, 48 for COSO-based TRNG, and two for STR-based TRNG, respectively.

True random number generators (TRNG) are widely used to generate encryption keys in information security systems [1]–[2]. In TRNG, entropy source is a critical module who provides the source of randomness of output bit stream. The unavoidable electrical noise in circuit becomes an ideal entropy source due to its unpredictability. Among the methods of capturing electrical noise, ring oscillator-based entropy source makes the TRNG most robust to deterministic noise and 1/f noise which means the strongest anti-interference capability, so it is simple in structure and easy to integrate [3]. Thus, great research attention has focused on ring oscillator-based TRNGs [3] –[7]. In [4], a high-speed TRNG with 100Mbps output bit rate was proposed, but it took up too much power and area. A TRNG based on tetrahedral ring oscillator was proposed in [5]. Its power consumption was very low but the output bit rate was also very low. A ring oscillator-based TRNG with low output bit rate but high power was proposed in [7]. In a word, none of the above architectures achieve an appropriate compromise between bit rate and power consumption. This work presents a new feedback architecture of TRNG based on tetrahedral ring oscillator. The output random bit stream generates a relative random control voltage that acts on the transmission gates in oscillator through a feedback loop, thus increasing phase jitter of the oscillator and improving output bit rate. Furthermore, an XOR chain-based post-processing unit is added to eliminate the statistical deviations and correlations between raw bits.

**Please read the paper on the following link:** https://ieeexplore.ieee.org/document/9145702 **Abstract:** This work presents a true random number generator (TRNG) based on a stochastic delta-sigma modulator (DSM) with ring oscillator (RO) integrators. The TRNG leverages noise and jitter in the ROs as an entropy source. A multi-bit non-return to- zero (NRZ) digital-to-analog converter (DAC) in the feedback path ensures DSM noise dominates input swing seen by the frontend integrators. Hence, the DSM can concurrently operate as an ADC and TRNG. A 65nm prototype achieves Shannon entropy > 0.999998 with lower-bound min-entropy > 0.995 at 52Mbps throughput while passing all NIST tests across multiple chips and voltage/temperature corners without needing calibration. The combined power consumption of ADC and TRNG is 0.36mW which is the lowest among state-of-the-art RO TRNGs. Low power consumption, high entropy, and concurrent operation of the TRNG as an ADC are principal contributions of this work.

<sec>Continuous-variable quantum random number generator (cv-QRNG) has attracted much attention due to its convenient state preparation and high measurement bandwidth. Chip-size integration of this type of QRNG is expectable because all components involved have been integrated on a single chip recently. Most of the existing schemes, including all existing commercial schemes, usually use a once-and-for-all approach to evaluate quantum entropy. In this work, we propose a double-level parallel cv-QRNG scheme that integrates real-time phase-space monitoring and entropy evaluation. By using dynamic threshold monitoring and self-adapting scaling of Toeplitz matrix, the security and generation rate of QRNG can be enhanced simultaneously.</sec><sec>Experimentally, a parallel extraction system of vacuum state double quadratures and multiple sideband modes is constructed based on heterodyne, providing sufficient raw data for high-precision and high-speed tomography reconstruction of quantum entropy source and parallel extraction of QRNG. Based on the statistical analysis of data under long-term stable operation of the system, dynamic KLD-sensitive security threshold for statistical distribution of Husimi-Q function of the entropy source is established. When a weak chaotic field is injected to simulate a thermal state attack, the KLD value jumps and quickly deviates from the steady state baseline, manifesting a sensitive identification of the attack. It is worth pointing out that the threshold parameter can be dynamically optimized according to the security requirements of actual application scenarios. An FPGA-based real-time feedback Toeplitz-hash extractor employs a maximum matrix bit-width truncation method to dynamically adjust Toeplitz matrix parameters. This optimization reduces the maximum extraction ratio interval from 6% to 1.8%, with all intervals below 1% for extraction ratios <i>≤</i>76%, significantly mitigating entropy losses caused by discrete adjustment of the Toeplitz matrix, and achieving a minimum extraction ratio of 16.9%. This flexibility enables the system to accurately control the response sensitivity of abnormal signals while maintaining the real-time generation of quantum random bits. Finally, real-time generation rate of 17.512 Gbit/s is attained with security parameters at the level of 10<sup>–50</sup> and the generated random numbers passed NIST SP 800-22, Diehard, and TestU01 standard tests.</sec><sec>This research provides a technical path for real-time assessment of entropy source security in QRNG. The proposed scheme has good integrability and scalability, presenting a feasible solution for QRNG to enter the application stage.</sec>

Random numbers are at the heart of diverse fields, ranging from simulations of stochastic processes to classical and quantum cryptography. The requirement for true randomness in these applications has motivated various proposals for generating random numbers based on the inherent randomness of quantum systems. The generation of true random numbers with arbitrarily defined probability distributions is highly desirable for applications, but it is very challenging. Here we show that single-photon quantum walks can generate multi-bit random numbers with on-demand probability distributions, when the required “coin” parameters are found with the gradient descent (GD) algorithm. Our theoretical and experimental results exhibit high fidelity for various selected distributions. This GD-enhanced single-photon system provides a convenient way for building flexible and reliable quantum random number generators. Multi-bit random numbers are a necessary resource for high-dimensional quantum key distribution.

Random numbers are a fundamental resource in science and engineering, and are also widely used in many fields, such as simulation, cryptography, lotteries, fundamental science. There are algorithmically generated numbers that look like random numbers but are not truly random. These pseudo random numbers are generated from a computer, using deterministic algorithms. Because, we cannot use pseudo random generators in situations, where true randomness is necessary, we use true random number generators. In this case, we use unpredictable random events as a random source. Quantum random number generators (QRNG) output true random numbers based on inherent randomness in quantum measurements. Our goal is to generate fast random numbers at a lower cost. At the same time, a high level of randomness is essential. We present the improved novel quantum random number generator, which is based the on time of arrival QRNG. It is rather efficient, as it uses the simple version of the detectors with rather few requirements. The novel QRNG produces more than one random bit per each photon detection.

A 10-Gb/s throughput all-digital true-random-number generator (TRNG) is introduced. The TRNG comprises an entropy source based on a StrongARM latch comparator and a post-processing block using the middle square method (MSM). The comparator is fully digital, so the entropy source can operate at a high frequency with robustness to process-voltage-temperature (PVT) variation. The MSM post-processing effectively removes any colored noise from the entropy source. The randomness of the MSM post-processing is evaluated by machine-learning resistance. The prototype TRNG is fabricated in a 28-nm CMOS process, and the measurement shows a 10-Gb/s throughput with a power efficiency of 0.121 pJ/bit. The output random bit stream passed all the NIST SP 800-22 and NIST SP 800-90B tests under various operating conditions with a maximum Shannon entropy of 0.999999999997.

Currently, True Random Number Generation (TRNG) is relatively slow, utilizing natural, physical processes as its entropy source. Other types of random numbers, such as Pseudo-Random Numbers, lack true randomness as eventually they repeat, but can be generated with great speed. The main idea of the work presented in this paper is to introduce parallel random number generation as a scalable means of increasing the rate of true random number generation in hardware to match and surpass that of Pseudo-Random Number Generators (PRNGs). Using a Raspberry Pi platform, this work will combine two (2) standard TRNGs to form one (1) unified, Parallel - True Random Number Generator (P-TRNG), with more than twice the output performance rate of its component TRNGs, and with demonstrated scalability.

In this paper, we propose and demonstrate a novel technique for true random number generator (TRNG) application using GeSe-based Ovonic threshold switching (OTS) selector devices. The inherent variability in OTS threshold voltage results in a bimodal distribution of on/off states which can be easily converted into digital bits. The experimental evaluation shows that the proposed TRNG enables the generation of high-quality random bits that passed 12 tests in the National Institute of Standards and Technology statistical test suite without complex external circuits for post-processing. The randomness is further evidenced by the prediction rate of ∼50% using machine learning algorithm. Compared with the TRNGs based on non-volatile memories, the volatile nature of OTS avoids the reset operation, thus further simplifying the operation and improving the generation frequency.

A true random number generator (TRNG) is essential to ensure information security for Internet of Things (IoT) edge devices. While pseudorandom number generators (PRNGs) have been instrumental, their deterministic nature limits their application in security-sensitive scenarios. In contrast, hardware-based TRNGs derived from physically unpredictable processes offer greater reliability. This study demonstrates a peripheral-free TRNG utilizing two cascaded three-stage inverters (TSIs) in conjunction with an XOR gate composed of monolayer molybdenum disulfide (MoS2) field-effect transistors (FETs) by exploiting the stochastic charge trapping and detrapping phenomena at and/or near the MoS2/dielectric interface. The entropy source passes the NIST SP800-90B tests with a minimum normalized entropy of 0.8780, while the generated bits pass the NIST SP800-22 randomness tests without any postprocessing. Moreover, the keys generated using these random bits are uncorrelated with near-ideal entropy, bit uniformity, and Hamming distances, exhibiting resilience against machine learning (ML) attacks, temperature variations, and supply bias fluctuations with a frugal energy expenditure of 30 pJ/bit. This approach offers an advantageous alternative to conventional silicon, memristive, and nanomaterial-based TRNGs as it obviates the need for extensive peripherals while harnessing the potential of atomically thin 2D materials in developing low-power TRNGs.

We present the results of the detected voltage distribution of a quantum random number generator (QRNG) based on a photonic integrated circuit comprising a semiconductor laser, delay interferometer and photodetector. We find that the integrated QRNG system behaves as expected for a QRNG from discrete gain-switched laser sources, especially exhibiting all of the peculiarities of the random voltage distribution and behaving as previously demonstrated for a discrete optical component setup. The biggest advantage of having all of the components integrated into a single chip is that only electrical connections are needed to operate the system, without the need for tricky and expensive optical alignment to external circuitry. We supply results showing that a random bit stream created from the random numbers passes the NIST statistical test suite tests, thus demonstrating the feasibility to generate random numbers via quantum means at gigabit/s rates from a single photonic integrated circuit. All of our results are backed by numerical simulations.

In this paper, we propose a Ferroelectric Tunnel Junction (FTJ)-based true random number generator (TRNG) that utilizes the stochastic domain switching phenomenon in ferroelectric materials. Ferroelectrics are promising for extracting randomness owing to their innate switching entropy in the multi-domain state. The random numbers generated by the proposed TRNG are shown to pass all the NIST SP 800-22 tests. The robustness of the proposed TRNG is also validated at various temperature and process corners. Important metrics such as power, bit rate, and energy/bit are calculated. This is the first comprehensive work demonstrating a ferroelectric-based TRNG with all these metrics. Compared to state-of-the-art TRNGs using other emerging technologies, we can achieve a higher bit rate with lower power consumption. We also perform material-level optimization with different ferroelectric materials, and showcase the trade-off between the bit rate and the power consumption. The proposed TRNG shows high robustness and reliability, and thus has the potential for implementing a low power on-chip solution.

We demonstrate a novel high speed and multi-bit optical quantum random number generator by continuously measuring arrival time of photons with a common starting point. To obtain the unbiased and post-processing free random bits, the measured photon arrival time is converted into the sum of integral multiple of a fixed period and a phase time. Theoretical and experimental results show that the phase time is an independent and uniform random variable. A random bit extraction method by encoding the phase time is proposed. An experimental setup has been built and the unbiased random bit generation rate could reach 128 Mb/s, with random bit generation efficiency of 8 bits per detected photon. The random numbers passed all tests in the statistical test suite.

Quantum random number generator (QRNG) allows obtaining true random bit sequences. In QRNG based on quantum nature of vacuum, optical beam splitter with two inputs and two outputs is normally used. We compare mathematical descriptions of spatial beam splitter and fiber Y-splitter in the quantum model for QRNG, based on homodyne detection. These descriptions were identical, that allows to use fiber Y-splitters in practical QRNG schemes, simplifying the setup. Also we receive relations between the input radiation and the resulting differential current in homodyne detector. We experimentally demonstrate possibility of true random bits generation by using QRNG based on homodyne detection with Y-splitter.

By measuring the amplified spontaneous emission (ASE) noise of the superluminescent light emitting diodes, we propose and realize a quantum random number generator (QRNG) featured with practicability. In the QRNG, after the detection and amplification of the ASE noise, the data acquisition and randomness extraction which is integrated in a field programmable gate array (FPGA) are both implemented in real-time, and the final random bit sequences are delivered to a host computer with a real-time generation rate of 1.2 Gbps. Further, to achieve compactness, all the components of the QRNG are integrated on three independent printed circuit boards with a compact design, and the QRNG is packed in a small enclosure sized 140 mm × 120 mm × 25 mm. The final random bit sequences can pass all the NIST-STS and DIEHARD tests.