IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT)
True Random Number Generators for Batch Control Sampling in Smart Factories
Leonardo Costa Ribeiro, Ana C. O. Marcelino, G A Garcia, Desiree S. Goncalves, Luiz Vicente Gomes Tarelho, Leandro P. Correa, Wladmir Araújo Chapetta, Alan Oliveira de Sá, Raphael C. S. Machado
This paper presents the assembling of a simple photo quantum true random number generator that can be easily adapted to provide a web service for randomness beacon. The sampling stage for monitoring and controlling a line production in Industry 4.0 should be certifiable and easily inserted in the process control. This certification is required due to total quality control management and the easibility aspect is due to the evolving automation of machines and devices in the production process. The randomness of the batch control can be physically and intrinsically verifiable and certifiable by using the service that will be offered by using the device presented here.
This paper presents the assembling of a simple photo quantum true random number generator that can be easily adapted to provide a web service for randomness beacon. The sampling stage for monitoring and controlling a line production in Industry 4.0 should be certifiable and easily inserted in the process control. This certification is required due to total quality control management and the easibility aspect is due to the evolving automation of machines and devices in the production process. The randomness of the batch control can be physically and intrinsically verifiable and certifiable by using the service that will be offered by using the device presented here.
Random numbers have many uses, but finding true randomness is incredibly difficult. Therefore, quantum mechanics is used, using the essentially unpredictable behavior of a photon, to generate truly random numbers that form the basis of many modern cryptographic protocols. It is essential to trust cryptographic random number generators to generate only true random numbers. This is why certification methods are needed which will check both the performance of our device and the quality of the random bits generated. Self-testing as well as device independent quantum random number generation methods are analyzed in the paper. The advantages and disadvantages of both methods are identified. The model of a novel semi self-testing certification method for quantum random number generators is offered in the paper. This method combines different types of certification approaches and is rather secure and efficient. The method is very important for computer science, because it combines the best features from selftesting and device independent methods. It can be used, when the random numbers’ entropy depends on the device and when it does not. In the related researches, these approaches are offered to be used separately, depending on the random number generator. The offered novel certification technology can be properly used, when the device is compromised or spoiled. The technology can successfully detect unintended irregularities, operational problems, abnormalities and problems in the randomization process. The offered mythology assists to eliminate problems related to physical devices. The offered system has the higher certification randomness security and is faster than self-testing approaches. The method is rather efficient because it implements the different certification approaches in the parallel threads. The offered techniques make the offered research must more efficient than the other existing approaches. The corresponding programming simulation is implemented by means of the simulation techniques.
Randomness is an invaluable resource in today's life with a broad use reaching from numerical simulations through randomized algorithms to cryptography. However, on the classical level no true randomness is available and even the use of simple quantum devices in a prepare-measure setting suffers from lack of stability and controllability. This gave rise to a group of quantum protocols that provide randomness certified by classical statistical tests -- Device Independent Quantum Random Number Generators. In this paper we review the most relevant results in this field, which allow the production of almost perfect randomness with help of quantum devices, supplemented with an arbitrary weak source of additional randomness. This is in fact the best one could hope for to achieve, as with no starting randomness (corresponding to no free will in a different concept) even a quantum world would have a fully deterministic description.
Random number generators (RNG) are essential elements in many cryptographic systems. True random number generators (TRNG) rely upon sources of randomness from natural processes such as those arising from quantum mechanics phenomena. We demonstrate that a quantum computer can serve as a high-quality, weakly random source for a generalized user-defined probability mass function (PMF). Specifically, QC measurement implements the process of variate sampling according to a user-specified PMF resulting in a word comprised of electronic bits that can then be processed by an extractor function to address inaccuracies due to non-ideal quantum gate operations and other system biases. We introduce an automated and flexible method for implementing a TRNG as a programmed quantum circuit that executes on commercially-available, gate-model quantum computers. The user specifies the desired word size as the number of qubits and a definition of the desired PMF. Based upon the user specification of the PMF, our compilation tool automatically synthesizes the desired TRNG as a structural OpenQASM file containing native gate operations that are optimized to reduce the circuit’s quantum depth. The resulting TRNG provides multiple bits of randomness for each execution/measurement cycle; thus, the number of random bits produced in each execution is limited only by the size of the QC. We provide experimental results to illustrate the viability of this approach.
Even if the output of a Random Number Generator (RNG) is perfectly uniformly distributed, it may be correlated to pre-existing information and therefore be predictable. Statistical tests are thus not sufficient to guarantee that an RNG is usable for applications, e.g., in cryptography or gambling, where unpredictability is important. To enable such applications a stronger notion of randomness, termed "true randomness", is required, which includes independence from prior information. Quantum systems are particularly suitable for true randomness generation, as their unpredictability can be proved based on physical principles. Practical implementations of Quantum RNGs (QRNGs) are however always subject to noise, i.e., influences which are not fully controlled. This reduces the quality of the raw randomness generated by the device, making it necessary to post-process it. Here we provide a framework to analyse realistic QRNGs and to determine the post-processing that is necessary to turn their raw output into true randomness.
Abstract Quantum random numbers distinguish themselves from others by their intrinsic unpredictability arising from the principles of quantum mechanics. As such they are extremely useful in many scientific and real-world applications with considerable efforts going into their realizations. Most demonstrations focus on high asymptotic generation rates. For this goal, a large number of repeated trials are required to accumulate a significant store of certifiable randomness, resulting in a high latency between the initial request and the delivery of the requested random bits. Here we demonstrate low-latency real-time certifiable randomness generation from measurements on photonic time-bin states. For this, we develop methods to certify randomness taking into account adversarial imperfections in both the state preparation and the measurement apparatus. Every 0.12 s we generate a block of 8192 random bits which are certifiable against all quantum adversaries with an error bounded by 2 −64 . Our quantum random number generator is thus well suited for realizing a continuously-operating, high-security and high-speed quantum randomness beacon.
Generating random bit streams is required in various applications, most notably in cyber-security, which is essential for Internet of Everything applications to enable secure communication between interconnected devices. Ensuring high-quality and robust randomness is crucial to mitigate risks associated with predictability and system compromise. True random numbers provide the highest levels of unpredictability. However, known systematic biases that can emerge from physical imperfections, environmental variations, and device aging in the processes exploited for random number generation must be carefully monitored. This article reports the implementation and characterization of an online procedure for the detection of anomalies in a true random bit stream. It is based on the NIST adaptive proportion and repetition count tests, complemented by statistical analysis relying on the Monobit and RUNS tests. The procedure is implemented in firmware through dedicated hardware accelerators processing configurable-length sequences, with automated anomaly detection triggering alerts after three consecutive threshold violations. The implementation is performed simultaneously with bit stream generation and also provides an estimate of the entropy of the source. A statistical analysis of the results from the NIST procedure to evaluate the symbols of the bit-stream as independently and identically distributed is also performed, leading to a computation of the minimum entropy of the source that cross-checks the previously mentioned estimate. The experimental validation of the approach is performed up the bit streams generated by a quantum, silicon-based entropy source.