True-Randomness and Pseudo-Randomness in Ring Oscillator-Based True Random Number Generators

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.

Many side channels including power consumption, electromagnetic emanation, optical radiation, and even sound have been studied since the first publication of a side channel attack at the end of the 1990s. Most of these channels can be relatively easily used for an overall analysis of the cryptographic system (implementation of efficient passive attacks) or for injection of faults. Until recently, only the optical channel allowed both analysis of locally leaked information and precise injection of faults (single-bit errors). Recent works showed that the near-field electromagnetic channel enables similar results to be obtained. Like the optical channel, the near-field electromagnetic channel allows both active and passive attacks, which, in addition, can be theoretically non-invasive and contactless. However, the cost of the attack bench that is needed to exploit the near-field electromagnetic channel is less than that of an optical channel. Recently, we showed that it is possible to use the near-field electromagnetic channel to perform an efficient active attack targeting the true random number generator (TRNG) based on ring oscillators. In cryptography, TRNGs are chiefly used to generate encryption keys and other critical security parameters, so the proposed active attack could have serious consequences for the security of the whole cryptographic system. Here, we present the coupling of a passive attack and an active attack. The proposed coupled attack first uses a spectral differential analysis of the TRNG electromagnetic radiation to obtain valuable information on the position of ring oscillators and their frequency range. This information is then used to tune the electromagnetic harmonic signal to temporarily synchronize the ring oscillators. In this paper, we propose a fault model of the entropy extractor which shows that the behavior of the ring oscillators changes, and that it occurs additional and unwanted “fake rising edges” of the clock signal which disturb the flip-flops involved in such TRNGs. The effectiveness of our proposed coupled attack questions the use of ring oscillators in the design of TRNGs.

In this paper, we provide a complete set of algorithms aimed at the design and security evaluation of oscillator-based True Random Number Generators (TRNG). While depending on some TRNG design assumptions, the proposed algorithms use as inputs the statistical parameters of the underlying random physical process such as the clock jitter originating from the thermal noise and give a lower bound of the entropy rate of the generated bit stream as output. We describe the general structure of a TRNG composed of multiple free-running oscillators and samplers, the outputs of which are post-processed by an entropy conditioner. Depending on the specification of the entropy conditioner, which can usually be any Boolean function, we describe several algorithmic optimizations. We then explain how to compute and efficiently manage the entropy rate at the output of such a post-processing block and at the output of the generator as a whole.

The design of a meta-stable ring oscillator-based true random number generator (TRNG) is presented in this paper. The proposed circuit is designed in 40nm CMOS technology and simulated in cadence virtuoso simulation environment using a combination of current starved-based ring oscillators (ROs), multiplexer, linear feedback shift register (LFSR), UP/DOWN counter followed by a meta-stable circuit. The current starved inverter-based RO is used in place of the power-hungry comparator to save a significant amount of power dissipation observed in the existing design. The metastable circuit is used for providing randomness in the design. The proposed design had resulted in the generation of approximately 40Mbps speed, the power dissipation of 730μW, and energy efficiency of 18.25pJ/bit when designed at 1.1V. The design is fully validated by NIST 800.22 statistical test suite. The proposed design is thus highly suitable for random number generation.

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.

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.

Printed electronics (PE) is a fast-growing field with promising applications in wearables, smart sensors, and smart cards, since it provides mechanical flexibility, and low-cost, on-demand, and customizable fabrication. To secure the operation of these applications, true random number generators (TRNGs) are required to generate unpredictable bits for cryptographic functions and padding. However, since the additive fabrication process of the PE circuits results in high intrinsic variations due to the random dispersion of the printed inks on the substrate, constructing a printed TRNG is challenging. In this article, we exploit the additive customizable fabrication feature of inkjet printing to design a TRNG based on electrolyte-gated field-effect transistors (EGFETs). We also propose a printed resistor tuning flow for the TRNG circuit to mitigate the overall process variation of the TRNG so that the generated bits are mostly based on the random noise in the circuit, providing a true random behavior. The simulation results show that the overall process variation of the TRNGs is mitigated by 110 times, and the generated bitstream of the tuned TRNGs passes the National Institute of Standards and Technology - Statistical Test Suite. For the proof of concept, the proposed TRNG circuit was fabricated and tuned. The characterization results of the tuned TRNGs prove that the TRNGs generate random bitstreams at the supply voltage of down to 0.5 V. Hence, the proposed TRNG design is suitable to secure low-power applications in this domain.

Random numbers are widely used in the cryptography and security systems. However, most of the true random number generators (TRNG) which use physical randomness are with high complexity and high power consumption. This paper proposes a new TRNG circuit using magnetic tunnel junction (MTJ). As one of the reliability issues in MTJ based circuit, the stochastic switching behavior provides a perfect physical source of randomness. The functionality of proposed design is validated by transient simulations with 28nm fully depleted silicon-on-insulator (FDSOI) technology and an accurate MTJ compact model. Simulation results show that our design can generate accurate random bitstream stably. The reliability analysis concerning process variation of MTJs and transistors proves the good variability tolerance of our TRNG design. Furthermore, our design can output stable random bitstream around 30 tuning steps.

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.

Quantum random number generators (QRNG) represent an advanced solution for randomness generation, which is essential in every cryptographic application. In this context, integrated arrays of single-photon detectors have promising applications as QRNGs based on the spatial detection of photons. For the employment of QRNGs in cryptography, it is necessary to have efficient methods to evaluate the so-called quantum min-entropy that corresponds to the amount of the true extractable quantum randomness from the QRNG. Here, we present an efficient method that allows the estimation of the quantum min-entropy for a multi-detector QRNG. In particular, we consider a scenario in which an attacker can control the efficiency of the detectors and knows the emitted number of photons. Eventually, we apply the method to a QRNG with 103 detectors.

We present a validation and test methodology for a non-deterministic system, namely a True Random Number Generator (TRNG). The TRNG testing methods at Intel have matured over time, and what we present here is the 3rd generation methodology used in our latest chipset products. In addition to well known DFT and DFV techniques, testing of a TRNG requires rigorous statistical analysis to determine its proper operation. Known published works and standards donpsilat address the TRNG testing and validation issues in high volumes or their recommendations are impractical in real manufacturing constraints. We present a practical statistical methodology for TRNG testing in a high volume manufacturing environment. Its validity was proven by testing a 65-nm CMOS-based TRNG design to meet NIST standards. Our methodology can be extended to the testing of similar non-deterministic systems.

Random numbers are widely used in cryptographic algorithms and protocols. A faulty true random number generator (TRNG) may open a door into a system in spite of cryptographic protection. It is therefore important to design TRNGs so that they can be tested at different stages of their lifetime to assure their trustworthiness. In this paper, we propose a method for designing physical unclonable function (PUF)-based TRNGs which can be tested in-field by known answer tests. We present a prototype FPGA implementation of the proposed TRNG based on an arbiter PUF which passes all NIST 800-22 statistical tests and has the minimal entropy of 0.918 estimated according to NIST 800-90B recommendations. This is a nontrivial achievement given that arbiter PUFs are notoriously hard to place in a symmetric manner in FPGAs.

True random numbers are essential for ensuring information security and supporting simulations across various industries. With the exponential growth of data driven by advancements in artificial intelligence, robust encryption for communications has become increasingly important. While software-based deterministic random number algorithms are cost-effective and easy to use, they are vulnerable to attacks by powerful supercomputers, highlighting the need for more secure alternatives. As portable electronic devices and information-gathering sensors proliferate, portable true random number generators (TRNGs) are critical for maintaining security. In this work, hybrid material-based photodetectors composed of anionic polymers and perovskites that maximize stochastic photogeneration for TRNG applications are presented. By integrating perovskite photodetectors with simple electronic circuits, compact, low-power TRNG devices have been developed that are versatile and resilient to environmental factors. These devices generate 10000 bitss-1 without resets or delays, achieving significant miniaturization. The generated 10 Mbit random number is validated through US National Institute of Standards and Technology (NIST) testing. Using a 480000-bit random sequence, perfect image encryption, ensuring protection against hacking are demonstrated. Additionally, the perovskite TRNG can operate under external light even when embedded in pork skin, realizing its potential as an implantable device for personal security and authentication.

A TRNG (True Random Number Generator) is an important component for security in mobile computing and IoT. This paper presents an light-weight FPGA implementation of a previously proposed latch-based TRNG, while keeping the quality of generated random numbers. By accumulating the generated random numbers fifteen times with an XOR operation for each output word, the proposed TRNG with 16 latches passed the NIST SP 800-22 test suite, whereas the original TRNG required 248 latches. An important finding of this work is that the quality of random sequence is greatly improved by XOR-ing temporally interleaved series of bits.

The generation of random numbers is crucial for practical implementations of cryptographic algorithms. In this sense, hardware security modules (HSMs) include true random number generators (TRNGs) implemented in hardware to achieve good random number generation. In the case of cryptographic algorithms implemented on FPGAs, the hardware implementation of RNGs is limited to the programmable cells in the device. Among the different proposals to obtain sources of entropy and process them to implement TRNGs, those based in ring oscillators (ROs), operating in parallel and combined with XOR gates, present good statistical properties at the cost of high area requirements. In this paper, these TRNGs are revisited, showing a method for area optimization independently of the FPGA technology used. Experimental results show that three ring oscillators requiring only three LUTs are enough to build a TRNG on Artix 7 devices from Xilinx with a throughput of 33.3 Kbps, which passes NIST tests. A throughput of 50 Kbps can be achieved with four ring oscillators, also requiring three LUTs in Artix 7 devices, while 100 Kbps can be achieved using an structure with four ring oscillators requiring seven LUTs.