Data Analysis Methods Preliminaries for a Photon-based Hardware Random Number Generator

TL;DR

This paper discusses the importance of high-quality random numbers for security and scientific applications, emphasizing the advantages of hardware random number generators over pseudo-random methods, especially in cryptography.

Contribution

It introduces the preliminary data analysis methods for a photon-based hardware random number generator, highlighting its potential for generating secure, high-quality random numbers.

Findings

Photon-based HRNG can produce high-quality randomness.

Hardware RNGs are less predictable than PRNGs.

Potential for high-speed secure random number generation.

Abstract

High quality random numbers are necessary in the modern world. Ranging from encryption keys in cyber security to models and simulations for scientific use: it's important that these random numbers are of high quality and quickly attainable. One common solution to the generation of random numbers is that of pseudo-random number generators, or PRNGs. PRNGs generate random numbers by first quantifying some unpredictable phenomena into a number or string and feeding it into an algorithm which yields numbers randomly based on that seed. Easy places to find seeds include the user's mouse movements or the machine's uptime. These are only pseudorandom, however, as if given the same seed twice, the PRNG would generate the same 'random' output. This is great for games like Minecraft, but not so great for cybersecurity encryption key generation. By using a hardware random number generator (HRNG), random numbers that are not susceptible to the flaws found in PRNGs can be attained at a high rate.