True Random Number Generator Research Articles

Jitter-Quantizing-Based TRNG Robust Against PVT Variations

Security is critical to the growing popularity of the Internet of Things(IoT), and true random number generator (TRNG) plays an increasingly important role in information security systems. Conventional TRNGs use natural physical stochastic processes including thermal noise, chaos-based circuit, and so on to generate random numbers. These analog circuits based TRNG structures often consume excessive hardware resources. Meanwhile, it is difficult to incorporate them into digital system. In this paper, a novel all-digital true random number generator in SRAM-based FPGAs is proposed by using Vernier technique that precisely quantize random edge jitter. The proposed TRNG design is implemented on Xilinx Virtex-6 XC6VLX240T-1FF1156 FPGA and shows a high quality of randomness which has passed the NIST test suite with relatively high p-values, achieves a high throughput of 127 Mbps with occupying 32 slices. Experimental results show a good tolerance to bias phenomenon induced by process, voltage, and temperature variations.

A Unified Memory and Hardware Security Module Based on the Adjustable Switching Window of Resistive Memory

Physically unclonable function (PUF) and true random number generator (TRNG) are critical primitives to provide lightweight hardware protection. As area is tightly restricted in IoT applications, merging PUF and TRNG is a novel trend to achieve higher area efficiency. In this work, a novel tri-functional module is proposed and experimental demonstrated using RRAM for the first time. A two-phase forming process is designed to generate and store PUF ID utilizing the impact of different forming conditions on the switching window. As PUF ID is stored by the switching window, instead of a fixed resistance, PUF cells can be written to low resistance state and high resistance state as usual, and can be used as memory and TRNG. The inter-Hamming distance of the generated PUF IDs approaches 0.5, and with the majority voting readout strategy, low BER can be achieved in a wide range of temperatures from −40°C to 125°C. TRNG produces the true random numbers based on the parity of the number of pulses consumed in a write-zero process. The generated random numbers are uniform and uncorrelated after XORed, and the statistical randomness is verified by NIST SP800-22 tests.

A True Random Number Generator Based on Gait Data for the Internet of You

The Internet of Things (IoT) is more and more a reality, and every day the number of connected objects increases. The growth is practically exponential -there are currently about 8 billion and expected to reach 21 billion in 2025. The applications of these devices are very diverse and range from home automation, through traffic monitoring or pollution, to sensors to monitor our health or improve our performance. While the potential of their applications seems to be unlimited, the cyber-security of these devices and their communications is critical for a flourishing deployment. Random Number Generators (RNGs) are essential to many security tasks such as seeds for key-generation or nonces used in authentication protocols. Till now, True Random Number Generators (TRNGs) are mainly based on physical phenomena, but there is a new trend that uses signals from our body (e.g., electrocardiograms) as an entropy source. Inspired by the last wave, we propose a new TRNG based on gait data (six 3-axis gyroscopes and accelerometers sensors over the subjects). We test both the quality of the entropic source (NIST SP800-90B) and the quality of the random bits generated (ENT, DIEHARDER and NIST 800-22). From this in-depth analysis, we can conclude that: 1) the gait data is a good source of entropy for random bit generation; 2) our proposed TRNG outputs bits that behave like a random variable. All this confirms the feasibility and the excellent properties of the proposed generator.

True Random Number Generator for Reliable Hardware Security Modules Based on a Neuromorphic Variation-Tolerant Spintronic Structure

The generation of true random numbers is one of the most important tasks in a hardware security module (HSM), particularly for cryptography applications. The stochastic behavior of electronic devices can be used to generate random numbers. In this paper, a reliable neuromorphic true random number generator (TRNG) relying on stochastic switching of the magnetic tunnel junction (MTJ) in the subcritical current regime is proposed. Thanks to the efficient structure of the proposed design as well as the fascinating features of the MTJs and carbon nanotube field-effect transistors (CNTFET), the proposed TRNG consumes low power. Moreover, the neuromorphic structure of the proposed design leads to variation tolerance and guarantees the truly random number generation even in the presence of the process variations. HSPICE simulations verify the functionality of the proposed TRNG. Furthermore, by considering the corners of the fabrication process, the randomness of the bitstream, generated by the proposed TRNG, is validated by the statistical randomness test provided by the U.S National Institute of Standards and Technology (NIST).

Alteration of Gate-Oxide Trap Capture/Emission Time Constants by Channel Hot-Carrier Effect in the Metal-Oxide-Semiconductor Field-Effect Transistor

Electrical-stress-invariant gate-oxide traps' capture and emission time constants have been the basis of aging models as well as applications that leverage the stochastic nature of the capture and emission processes, such as the true random number generator. In this work, we show that this presumption is only valid for about two-thirds of the oxide-trap population studied. For the remaining one-third, the traps' capture and/or emission time constants could be changed by the channel hot-carrier (CHC) effect. Such a behavior is found in both polysilicon/silicon oxynitride gated and TiN/HfO2 gated transistors. A reversion of the altered trap time constant to the value before the CHC-stress is also observed, but the period varies significantly for different traps (from several hours to months). Since the CHC stress effect is present in all scaled transistors, the findings would have important implications for models/applications that presume oxide-trap properties to be stress-invariant.

An Innovative Near-Field Communication Security Based on the Chaos Generated by Memristive Circuits Adopted as Symmetrical Key

The new technology solutions are playing an important role in the hardware security. One of the latest techniques is the use of the Memristor as an encryption element. In this paper, it has been introduced a two-column array inductor for Memristor-Based Wireless Power Transfer (M-WPT) systems. The traditional WPT circuits are based on switches, which do require a control circuit for timing and have low data encryption factor. By adopting the memristive Chua`s circuit with the chaotic behaviour characteristic, it is possible to create a symmetrical dual-key cryptography. Furthermore, in this innovative solution, the high inductance value of the traditional Chua circuit can be further reduced by using the dynamic effects of the coils flux linkage. The simulation results exhibit the dual-scroll attractors phase portrait, which is available for encryption features. Therefore, the data collected from the phase portrait are used as true random number generator in Python code. Instead of using algorithms, the code can create a symmetrical key for an unique chaotic cryptography. In order to build a prototype, it has been created a PCB design for the whole system. The experiment highlights the unpredictable voltage and current and validates the chaotic behaviour of the transmitter and receiver.

True Random Number Generator Integration in a Resistive RAM Memory Array Using Input Current Limitation

A novel True Random Number Generator circuit fabricated in a 130 nm HfO2-based resistive RAM process is presented. The generation of the random bit stream is based on a specific programming sequence applied to a dedicated memory array. In the proposed programming scheme, all the cells of the memory array are addressed at the same time while the current provided to the circuit is limited to program only a subset of the memory array, resulting in a stochastic distribution of cell resistance values. Some cells are switched in a low resistive state, other cells are slightly programmed to reach an intermediate resistance state, while the remaining cells maintain their initial high resistance state. Resistance values are next converted into a bit stream and confronted to National Institute of Standards and Technology (NIST) test benchmarks. The generated random bit stream has successfully passed twelve NIST tests out of fifteen. Compared to state-of-the-art resistive RAM-based true random number generators, our proposed methodology is the first one to leverage on programming current limitation at a memory array level.

Amplified spontaneous emission based quantum random number generator

There is an increasing need for true random bits, for which true random number generators (TRNG) are absolutely necessary, because the output of pseudo random number generators is deterministically calculated from the previous states. We introduce our quantum number generator (QRNG) based on amplified spontaneous emission (ASE), a truly random quantum physical process. The experimental setup utilizes the randomness of the process. In this system, optical amplifiers (based on ASE) play the major role. The suitable sampling rate is selected in order to build the fastest generator, while avoiding the correlation between consecutive bits. Furthermore, the applied post-processing increases the quality of the random bits. As a results of this, our system generated random bits which successfully passed the NIST tests. Our real-time generation system – which is currently a trial version implemented with cheap equipment – will be available for public use, generating real time random bits using a web page.

Quantum Technology for Economists

Research on quantum technology spans multiple disciplines: physics, computer science, engineering, and mathematics. The objective of this manuscript is to provide an accessible introduction to this emerging field for economists that is centered around quantum computing and quantum money. We proceed in three steps. First, we discuss basic concepts in quantum computing and quantum communication, assuming knowledge of linear algebra and statistics, but not of computer science or physics. This covers fundamental topics, such as qubits, superposition, entanglement, quantum circuits, oracles, and the no-cloning theorem. Second, we provide an overview of quantum money, an early invention of the quantum communication literature that has recently been partially implemented in an experimental setting. One form of quantum money offers the privacy and anonymity of physical cash, the option to transact without the involvement of a third party, and the efficiency and convenience of a debit card payment. Such features cannot be achieved in combination with any other form of money. Finally, we review all existing quantum speedups that have been identified for algorithms used to solve and estimate economic models. This includes function approximation, linear systems analysis, Monte Carlo simulation, matrix inversion, principal component analysis, linear regression, interpolation, numerical differentiation, and true random number generation. We also discuss the difficulty of achieving quantum speedups and comment on common misconceptions about what is achievable with quantum computing.

Real-time Processing System for a Quantum Random Number Generator

Quantum random number generators (QRNG) provide quality random numbers, which are essential for cryptography by utilizing the unpredictable nature of quantum mechanics. Advancements in quantum optics made multiple different architectures for these possible. As part of a project aiming to realize a QRNG service, we developed a system capable of providing real-time monitoring and long term data collection while still fulfilling regular processing duties for these devices. In most cases, hardware validation is done by simply running a battery of statistical tests on the final output. Our goal, however, was to create a system allowing more flexible use of these tests, realizing a tool that can also prove useful during the construction of our entropy source for detecting and correcting unique imperfections. We tested this flexibility and the system’s ability to adequately perform the required tasks with simulated sources while further examining the usability of available verification tools within this new custom framework.

Testing Randomness Using Artificial Neural Network

The vital characteristic of randomness is unpredictability. Thus any regularity will compromise the application of random numbers. Quantum random number generators (QRNGs) can provide intrinsic unpredictable randomness based on the nature of quantum physics, while pseudo-random number generator can not due to the origination of deterministic algorithms or physical processes. However, commonly used traditional test suits are rigorously to test the statistical properties, and the unpredictability of random numbers is still difficult to test. To verify which sources of random numbers are truly unpredictable, in this paper, we propose a new randomness testing method with the artificial neural network (ANN). Random number sequences generated by four different kinds of sources are tested, which are the natural number λ, the linear congruence generator (LCG) pseudo-random algorithm, the Mersenne Twister (MT) pseudorandom algorithm and the QRNG based on vacuum noise, respectively. The testing results indicate that the random sequences from natural number λ and LCG fail to pass our randomness test, while the other two kinds of sequences pass the test successfully due to the relatively simple structure of our ANN. As the complexity of the ANN and the amount of computing power involved increasing, this test method has potential to predict the MT random numbers, and it is also expected that the quantum random numbers can not pass the test with unpredictability no matter how complex the ANN is.

Fully Synthesizable All-Digital Unified Dynamic Entropy Generation, Extraction, and Utilization Within the Same Cryptographic Core

This letter introduces a novel class of fully synthesizable all-digital true random number generators (TRNGs) using the same private-key cryptographic core for raw dynamic entropy generation, its extraction via post-processing, and its utilization as crypto-key for constrained secure systems. Endogenous random bit generation is achieved via clock pulsewidth overstretching in the digital implementation of private-key cryptographic algorithms using pulsed-latch pipelines, leveraging inherent Shannon confusion and diffusion. Demonstration on a 40-nm testchip based on a SIMON cryptographic core shows 64-bit key encryption down to 0.25 pJ/bit at 0.45 V, random number generation with cryptographic-grade entropy at 2.5 pJ/bit across manufacturing lots, dice, voltages, and temperature corners. The overall area is kept well below the 106 F2 area wall (F = minimum feature size).

Generation of 8 Gb/s physical random numbers based on spontaneous chaotic oscillation of GaAs/Al<sub>0.45</sub>Ga<sub>0.55</sub>As superlattices

<sec>Secret key is required in secure communications, and random numbers are generally used as keys to encrypt the original information. So it is crucial for cryptography and secure communication to generate the physical random number, which is completely safer than pseudo random number. However, Existing physical random number generator systems are difficult to satisfy the requirements of high-speed communication due to their complexity, large size, and limited equipment bandwidth. The GaAs/Al<sub>0.45</sub>Ga<sub>0.55</sub> superlattices is based on a structure formed by the alternating growth of two semiconductor materials, and has a good low-dimensional structure for studying the nonlinear behavior of electrons. Recent studies have shown that the GaAs/Al<sub>0.45</sub>Ga<sub>0.55</sub> superlattices under the DC voltage could appear chaos current oscillation states in some certain voltage ranges.</sec><sec>An all-solid-state real-time high-speed physical true random number generator based on superlattices is presented. The superlattices, excited by appropriate DC bias voltage, could generate a high-frequency chaotic oscillation signal as a source of physical entropy. A multi-bit analog-to-digital converter with 2 GHz sampling frequency is used for quantization to generate 12-bit binary random bits. Then, the field programmable gate array extracts the lowest 4 bits as valid bits and inverts bits to improve its randomness, and finally a true random number with a real-time rate of 8 Gbit/s is obtained. To obtained a superlattices signal with a higher degree of chaos, the Lyapunov exponent was used to assist in selecting a more suitable DC bias. The random number generated by the superlattices, owning excellent statistical characteristics, could pass the test of the random number industry standard (NIST SP 800-22), which is expected to be miniaturized and integrated on high-speed communication equipment.</sec>

A Low Power Circuit Design for Chaos-Key Based Data Encryption

Dynamic and non-linear systems have been used to generate random bits in high-security applications for decades. In this perspective, due to their stochastic characteristic, chaotic systems have been emerging as the natural choice for the generation of random bits. This paper presents the design and the implementation of a chaos-based true random number generator and a chaos-key based data encryption scheme for secure communications. The mathematical expression of the dynamic system is presented and analyzed to evaluate the possibility of chaos occurrence. Then, the chaotic system is realized at the circuit level using 130 nm CMOS technology to generate random bit sequences, which are utilized in data encryption. Chaotic signal outputs of the chaos-based random number generator circuit are sampled at a maximum frequency of 50 MHz, enabling a high throughput of random bits. The core of the chaotic circuit consumes $630~\mu \text{W}$ in static mode and a maximum of $660~\mu \text{W}$ in running mode. The chaos-based one-time pad encryption scheme using the chaos-key generator shows the advantages of using this random number generator in secure communications. In this context, the data secrecy is compared to the advanced encryption standard AES128. Moreover, the design is simulated in different working conditions such as voltage supply and temperature variations, where it is shown that the random bit output benefits from a high entropy per bit and passes the standard statistical test suite (NIST) for cryptographic applications.

Performance of Memristor Based Ring Oscillators True Random Number Generator for Energy Technology

We are living in an era where everything is trying to be more connected in terms of the different physical entities and its surrounding environment. This new concept that is developing called the Internet of Things (IoT) has garnered a lot of attention [Bodei, 2019 #45]. There are various of applications and smart objects associates with the IoT and this leads to an increase in security challenges. IoT security is very important but getting harder to achieve. One example of utilization of IoT is in the smart grid infrastructure and this in turn increases the need for network security. An integrated internet-based smart grid and energy resources also called Energy Internet (EI) has a lot of security challenges that comes with the current smart grid. Smart grid infrastructure and any means of energy that implements the internet system also known as Energy Internet (EI) has many security challenges that come with the current smart grid. A memristor based ring oscillator True Random Number Generator design has been proposed in this research as a solution that can combat security challenges that existed in the hardware implementation of devices. Inputs based on non-deterministic methods are being used in TRNGs to generate outputs that possessed randomness characteristics in applications of IoT that makes it secure. Complementary metal oxide semiconductor (CMOS) technology of 0.18 μm are being used in the TRNG design and a software of LT SPICE IV helps to realized it.The proposed TRNG design produced output that passed 10 out of the 15 NIST tests, therefore showed that the TRNG produce a fairly random output.

Self-testing quantum random-number generator based on an energy bound

We present a scheme for a self-testing quantum random number generator. Compared to the fully device-independent model, our scheme requires an extra natural assumption, namely that the mean energy per signal is bounded. The scheme is self-testing, as it allows the user to verify in real-time the correct functioning of the setup, hence guaranteeing the continuous generation of certified random bits. Based on a prepare-and-measure setup, our scheme is practical, and we implement it using only off-the-shelf optical components. The randomness generation rate is 1.25 Mbits/s, comparable to commercial solutions. Overall, we believe that this scheme achieves a promising trade-off between the required assumptions, ease-of-implementation and performance.

Parallel quantum random number generation based on spontaneous emission of alkaline earth

We propose a parallel quantum random number generator based on spontaneous emission of strontium atoms. By directly detecting the spontaneously emitted photons in different directions, two strings of true random bits with no apparent correlation at rates up to 5.12 Mb s−1 are simultaneously extracted. Via post-processing, both output sequences pass the NIST tests. Taking advantage of the random directions of the emitted photons, the presented scheme has great scalability to be extended to arbitrary multiple channels without limitations of devices’ demultiplexing configurations.

GeSe-Based Ovonic Threshold Switching Volatile True Random Number Generator

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

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.

A Survey on True Random Number Generators Based on Chaos

With the rapid development of communication technology and the popularization of network, information security has been highly valued by all walks of life. Random numbers are used in many cryptographic protocols, key management, identity authentication, image encryption, and so on. True random numbers (TRNs) have better randomness and unpredictability in encryption and key than pseudorandom numbers (PRNs). Chaos has good features of sensitive dependence on initial conditions, randomness, periodicity, and reproduction. These demands coincide with the rise of TRNs generating approaches in chaos field. This survey paper intends to provide a systematic review of true random number generators (TRNGs) based on chaos. Firstly, the two kinds of popular chaotic systems for generating TRNs based on chaos, including continuous time chaotic system and discrete time chaotic system are introduced. The main approaches and challenges are exposed to help researchers decide which are the ones that best suit their needs and goals. Then, existing methods are reviewed, highlighting their contributions and their significance in the field. We also devote a part of the paper to review TRNGs based on current-mode chaos for this problem. Finally, quantitative results are given for the described methods in which they were evaluated, following up with a discussion of the results. At last, we point out a set of promising future works and draw our own conclusions about the state of the art of TRNGs based on chaos.