Quantum random number generators and their use in cryptography

TL;DR

This paper reviews the importance of true quantum random number generators (TRNGs) in cryptography, compares quantum and classical RNGs, and explores the potential of mixed signal FPGA technology for quantum TRNG implementation.

Contribution

It provides a comparative analysis of quantum and classical RNGs and discusses the feasibility of implementing quantum TRNGs using emerging FPGA technology.

Findings

Quantum TRNGs offer provable randomness based on physical quantum systems.

Industry-standard RNGs based on electronic noise lack strict provability.

Mixed Signal FPGA technology could enable practical quantum TRNGs.

Abstract

Random number generators (RNG) are an important resource in many areas: cryptography (both quantum and classical), probabilistic computation (Monte Carlo methods), numerical simulations, industrial testing and labeling, hazard games, scientific research, etc. Because today's computers are deterministic, they can not create random numbers unless complemented with a RNG. Randomness of a RNG can be precisely, scientifically characterized and measured. Especially valuable is the information-theoretic provable RNG (True RNG - TRNG) which, at state of the art, seem to be possible only by use of physical randomness inherent to certain (simple) quantum systems. On the other hand, current industry standard dictates use of RNG's based on free running oscillators (FRO) whose randomness is derived from electronics noise present in logic circuits and which cannot be strictly proven. This approach is currently used in 3-rd and 4-th generation FPGA and ASIC hardware, unsuitable for realization of quantum TRNG. We compare weak and strong aspects of the two approaches and discuss possibility of building quantum TRNG in the recently appeared Mixed Signal FPGA technology. Finally, we discuss several examples where use of a TRNG is critical and show how it can significantly improve security of cryptographic systems.