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Australasian Journal of Paramedicine

Celestial sources for random number generation

Erin Chapman, Jerina Grewar, Tim J. Natusch

Published Jan 1, 2016• 2 citations
Publisher

Abstract

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.

DOI
10.4225/75/58a6975133e06

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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.
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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 numbers are indispensable for a variety of applications ranging from testing physics foundations to information encryption. In particular, nonlocality test provide strong evidence for our current understanding of nature-quantum mechanics. All the random number generators (RNGs) used for the existing tests are constructed locally, making the test results vulnerable to the freedom-of-choice loophole. We report an experimental realization of RNGs based on the arrival time of cosmic photons. The measurement outcomes (raw data) pass the standard NIST statistical test suite. We present a realistic design to employ these RNGs in a Bell test experiment, which addresses the freedom-of-choice loophole.
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.
We present a first random number generator (RNG) which simultaneously uses independent spatial and temporal quantum randomness contained in an optical system. Availability of the two independent sources of entropy makes the RNG resilient to hardware failure and signal injection attacks. We show that the deviation from randomness of the generated numbers can be estimated quickly from simple measurements thus eliminating the need for usual time-consuming statistical testing of the output data. As a confirmation it is demonstrated that generated numbers pass NIST Statistical test suite.