Random number generators (RNG) are important hardware primitives for many fields including secure communication, cryptology, weather forecast, gambling that needs unpredictable and non-deterministic random bit sequences. Various entropy sources are available to generate random numbers and generation rate depends on the application that needs to use random numbers. In this work, a new approach is given to generate random bits based on miniature microbial fuel cells that convert electrochemical energy into electricity. Microorganisms inside of the microbial fuel cell play a critical role to generate electricity therefore it is unpredictable what they will produce. An output voltage generated by the microbial fuel cells used to produce random bits then it was shown that they were successfully passed the NIST 800-22 statistical randomness tests after the XOR corrector post-processing method. The proposed approach can be especially used in environmental applications that need secure data transfer and bioreactors that have to securely send critical data to headquarter.
Random number generators (RNG) are important hardware primitives for many fields including secure communication, cryptology, weather forecast, gambling that needs unpredictable and non-deterministic random bit sequences. Various entropy sources are available to generate random numbers and generation rate depends on the application that needs to use random numbers. In this work, a new approach is given to generate random bits based on miniature microbial fuel cells that convert electrochemical energy into electricity. Microorganisms inside of the microbial fuel cell play a critical role to generate electricity therefore it is unpredictable what they will produce. An output voltage generated by the microbial fuel cells used to produce random bits then it was shown that they were successfully passed the NIST 800-22 statistical randomness tests after the XOR corrector post-processing method. The proposed approach can be especially used in environmental applications that need secure data transfer and bioreactors that have to securely send critical data to headquarter.
Cryptographic applications need high-quality random number generator (RNG) for strong security and privacy measures. This paper presents RNG based on a hydrogen gas sensor that is fabricated by using microfabrication techniques. The proposed approach extracts the thermal noise information as an entropy source from the gas sensor that is non-deterministic during its operation and using hash function SHA-256 as post processing. This non-deterministic noise is then processed to acquire a random number set fulfilling the NIST 800-22 statistical randomness test suite and it demonstrates that a gas sensor based RNG can provide high-quality random numbers. Secure data transfer is possible by having this method directly without any other hardware where hydrogen gas sensor needs to be used such as petrochemical field, fuel cells, and nuclear reactors.
The development of random number generators (RNGs) using speckle patterns is pivotal for secure encryption key generation, drawing from the recent statistical properties identified in speckle-based imaging. Speckle-based RNG systems generate a sequence of random numbers through the unpredictable and reproducible nature of speckle patterns, ensuring a source of randomness that is independent of algorithms. However, to guarantee their effectiveness and reliability, these systems demand a meticulous and rigorous approach. In this study, we present a blood-inspired RNG system with a microfluidics device, designed to generate random numbers at a rate of 5.5 MHz and a high-speed of 1250 fps. This process is achieved by directing a laser beam through a volumetric scattering medium to procure speckle patterns. Additionally, designed microfluidic device requires only a minimal blood sample of 5 µl to capture these speckle patterns effectively. After implementing the two-pass tuple-output von Neumann debiasing algorithm to counteract statistical biases, we utilized the randomness statistical test suite from the National Institute of Standards and Technology for validation. The generated numbers successfully passed these tests, ensuring their randomness and unpredictability. Our blood-inspired RNG, utilizing whole blood, offers a pathway for affordable, high-output applications in fields like encryption, computer security, and data protection.
In this paper, we design a photonic-based true random number generator (True RNG) which is targeted for cryptographic application .Since all security protocols rely on unpredictability, RNGs for crypto applications must meet stringent requirements. The design employs a single-photon detection to generate a random signal which is useful in producing random output. In contrast with traditionally used of frequency sampler circuitry during bit extraction method, it uses a novel method of randomness extraction based on time interval between two successive random signals. The design comprises an optical setup and extremely compact and digitally random bit extraction circuitry which can be implemented on any advance crypto hardware devices. A NIST statistical test is used to test the randomness of the RNG output and has produced a good result. With the help of this True RNG, the cryptographic implementations can be secure enough from being abused of malicious act.
Random numbers (RNs) have applications in many areas: lottery games, gambling, computer simulation, and, most importantly, cryptography [N. Gisin et al., Rev. Mod. Phys. 74 (2002) 145]. In cryptography theory, the theoretical security of the system calls for high quality RNs. Therefore, developing methods for producing unpredictable RNs with adequate speed is an attractive topic. Early on, despite the lack of theoretical support, pseudo RNs generated by algorithmic methods performed well and satisfied reasonable statistical requirements. However, as implemented, those pseudorandom sequences were completely determined by mathematical formulas and initial seeds, which cannot introduce extra entropy or information. In these cases, “random” bits are generated that are not at all random. Physical random number generators (RNGs), which, in contrast to algorithmic methods, are based on unpredictable physical random phenomena, have attracted considerable research interest. However, the way that we extract random bits from those physical entropy sources has a large influence on the efficiency and performance of the system. In this manuscript, we will review and discuss several randomness extraction schemes that are based on radiation or photon arrival times. We analyze the robustness, post-processing requirements and, in particular, the extraction efficiency of those methods to aid in the construction of efficient, compact and robust physical RNG systems.
Generation of random numbers is a central problem for many applications in the field of information processing, including, e.g., cryptography, in classical and quantum regime, but also mathematical modeling, Monte Carlo methods, gambling and many others. Both, the quality of the randomness and efficiency of the random numbers generation process are crucial for the most of these applications. Software produced pseudorandom bit sequences, though sufficiently quick, do not fulfill required randomness quality demands. Hence, the physical hardware methods are intensively developed to generate truly random number sequences for information processing and electronic security application. In the present paper we discuss the idea of the quantum random number generators. We also present a variety of tests utilized to assess the quality of randomness of generated bit sequences. In the experimental part we apply such tests to assess and compare two quantum random number generators, PQ4000KSI (of company ComScire US) and JUR01 (constructed in Wroclaw University of Science and Technology upon the project of The National Center for Research and Development) as well as a pseudorandom generator from the Mathematica Wolfram package. Finally, we present our new prototype of fully operative miniaturized quantum random generator JUR02 producing a random bit sequence with velocity of 1 Mb/s, which successfully passed standard tests of randomness quality (like NIST and Dieharder tests). We also shortly discuss our former concept of an entanglement-based quantum random number generator protocol with unconditionally secure public randomness verification.
One key requirement for many cryptograhic schemes is the generation of random numbers.Sequences of random numbers are used at several stages of a standard cryptographic protocol.One simple example is a Vernam cipher, where a string of random numbers is added to message string to generate encrypted code.C = M ⊕ K.It has been mathematically shown that this simple scheme is unbreakable if key K is as long as M and is used only once.The security of a cryptosystem shall not be based on keeping the algorithm secret but solely on keeping the key secret.The security of a random number generator (RNG) is related to the difficulty of predicting its future sequence values from past values.The quality and unpredictability of secret data is critical to securing communication by modern cryptographic techniques.The generation of such data for cryptographic purposes typically requires an unpredictable physical source of random data.We studied a chaotic circuit which consisted of an inductor, capacitance, diode and thus used for the BB84 protocol.We have studied both pseudo random and true random number generators and evaluated them through various tests like frequency, correlation, NIST etc.