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.
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.
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.
In this paper, we present an alternative method of gathering seed data for random number generation (RNG) in cryptographic applications. Our proposed method utilises the inherent randomness of signal data from celestial sources in radio astronomy to provide seeds for RNG. The data sets were collected from two separate celestial sources, and run through the SHA-256 algorithm to deskew the data and produce random numbers with a uniform distribution. The resulting data sets pass all tests in the NIST Statistical Test Suite for random data, with a mean of 98.9% of the 512 total bitstreams from the two sources passing all tests in the NIST suite, as well as further testing in R. These results are on par with the control set generated using Java’s SecureRandom function. An explanation of the sources, the data processing and detailed results of each of the tests are presented.
Unpredictability and entropy are key factors governing the success of cryptographic security, and true random numbers play a pivotal role in this space. While software-driven random numbers are easy and efficient to generate, their deterministic nature creates a vulnerability that could compromise the gate, barring entry to a sensitive system. Here, we propose using measurement randomness arising from physical and chemical aspects of transport (Layer 1), hardware characteristics (Layer 2), event features and extraction (Layer 3; facilitated by the HyperXtract 2.0), and cryptographic whitening via the secure hash algorithm (SHA-256; Layer 4) to create a high-entropy TRNG system. We demonstrate a host of unique experimental conditions (e.g., electrolyte chemistry, applied voltage, analyte type, transport direction, temperature, and amplifier type) across these four layers to generate ~480,000 256-bit long keys with 100% uniqueness in a Pearson-correlation-based statistical entropy harvesting method and most other methods reporting >99.9% unique keys in most instances. Furthermore, the randomness of these keys was evaluated using the NIST SP800-22b statistical test suite and yielded a success rate of ~99% at a 1% significance level. This study thus showcases the utility of solid-state nanopore sensing for generating high-entropy TRNGs and the potential as a robust, non-deterministic source for nextgeneration cybersecurity engineering.
Abstract Random numbers have significant applications in fundamental science, high-level scientific research, cryptography and several other areas where there is a pressing need for high-quality random numbers. We present an experimental demonstration of a non-deterministic random bit generator from a quantum entropy source and a deterministic random bit generator mechanism to provide high quality random numbers of 1 GB data size. Quantum entropy is realized by a series of quantum chips based on radioactive isotope Americium-241. The extracted raw random numbers are further post-processed to generate a high-entropy seed for the hash based deterministic random bit generator. We discuss the implementation of randomness extraction algorithm and Hash-DRBG algorithm in detail. The random numbers pass all the randomness measures provided in standard statistical test suites.
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.
Efficient and reliable Random Number Generator (RNG) are increasingly demanded in cryptographic applications, such as on-the-fly data encription/decription and as a general tool for data protection. Main requirement of RNG is a true randomness, which is achievable by means of physical randomness sources only. A True-RNG based on two independent Stochastic Processes (SP) is presented and discussed. As primary randomness sources, two radioactive decay processes are used. A radioactive source has many advantages over others noise sources, since the decay rate of any nuclide does not depend on temperature, chemical composition, physical state, environmental conditions, and aging. In addition, in U ore for example, the various nuclides are, at very good approximation, at equilibrium in the decay chain, so that many stationary independent SP's with the same statistics can be simply obtained by detecting and selectively routing, e.g. by pulse amplitude sorting, gamma rays of different energy emitted by different nuclides in the decay chain. Simulation is performed by a numerical code. The random bit stream obtained is tested for randomness by the NIST test suite, and results are shown. A hardware implementation of the system is also presented.