Editorial Feature

The Future of Hardware Encryption with Optical Quantum Random Number Generators

At the heart of quantum physics lies true randomness which can be exploited to create truly random number generation with applications in areas such as cybersecurity. 

quantum physics

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Quantum Dice, a UK start-up that spun out of Oxford University’s quantum optics lab, is developing the world's first compact source-device independent quantum random number generator (QRNG).

The company has raised $2.36m in funding for the QRNG which will use integrated photonics and will have applications in encryption and cybersecurity. 

Quantum optics focuses on the simplest quantum objects such as atoms and photons, the fundamental particles of light, and has grown from a niche field within physics to a broad research area. 

But what is it about quantum physics and quantum photonics that makes it ideal for random number generation and encryption?

The Randomness at the Heart of Quantum Physics

One of the most counterintuitive elements that scientists had to adapt regarding quantum mechanics upon its inception in the early years of the 20th century was the idea that quantum systems are completely random.

Until this point in the history of physics, physical systems had been considered deterministic. Run the same experiment twice under the same conditions and you get the same results. 

For instance, imagine the very simple experiment of flipping a coin. Carried out in the same conditions and with the same force, classical physics says that the result will be the same time and time again. Of course, this is difficult to achieve in practice because of the number of conditions that need to be controlled. 

This is not the case with quantum mechanics, the physics of the infinitesimally small. In this discipline of physics, it is possible to run the same experiment under identical conditions and get a different result. This is not just because of a range of conditions that need to be controlled. Quantum processes occur seemingly at random.

As we cannot flip a quantum coin, take the radioactive decay of an atom as an example. An atomic nucleus can emit energy in the form of alpha particles — helium nuclei — electrons and neutrons, also known as beta particles, or as gamma rays. 

These processes, alpha decay, beta decay, and gamma decay transform less stable elements and isotopes into more stable elements. There is no predicting when this will occur. Observe a single atom of an unstable element and it could decay in a fraction of a second, a week, a year, or several millennia. It is completely random. 

If enough atoms are gathered, and the matter is of course made of tremendously large numbers of atoms, scientists can build a statistical picture of how long it will take half of these atoms to decay.

This is the principle behind atomic half-lives and we have successfully parlayed that principle into remarkably efficient and precise dating methods for a variety of materials called radiometric dating.

It is the randomness of quantum physics we are interested in, however, not the way it builds a statistical picture. Since its discovery, scientists have been finding uses for randomness at the heart of the quantum world.

One of these applications of this randomness is in random number generation.

Random Number Generation and True Random Number Generation

There are currently two different types of random number generators, including true random number generators (TRNGs) and pseudo-random number generators (PRNGs) used in cryptography and cyber security. 

PRNGs rely on a deterministic process that produces strings of numbers that may seem random but are not. The algorithm creates a series of numbers based on a set seed value. A fixed seed will create the same series of numbers. This has several high-profile security breaches.

Current TRNGs exist and rely on several physical attributes such as atmospheric or thermal conditions to generate a random number sequence. But, like the coin flip example, in conditions that are the same, the same result could be produced. TRNGs take a deterministic way of generating random numbers and make it so complex that cracking them is implausible.

While much more secure than PRNGs, TRNGs take much longer to generate random number sequences. 

Rolling Quantum Dice

The team behind Quantum Dice is pioneering a solution for secure true randomness based on quantum optics. They hope that this will address the flaws with currently available technology.

CEO and co-founder of Quantum Dice, Dr. Ramy Shelbaya, says that the widespread belief that the current random number generation for cyber security is ‘good enough’ may be misplaced because it is currently difficult to quantify their security advantages. He believes Quantum Dice could change this and make quantum security accessible to all encryption applications.

At the heart of the company’s QRNG is a patented source-device independent self-certification (DISC) protocol, which allows live continuous verification of the security of the output numbers rather than simply relying on statistical analysis.

The DISC protocol was originally created in the Quantum Optics research group of Oxford professor Ian Walmsley. The initial QRNG prototype demonstrated a rapid generation rate of 8.05 Gbit/s of quantum-secure randomness, which is better than current TRNGs.

The funding raised by Quantum Dice will be used to expand its team of engineers, including experts in photonics. It will also help build upon Quantum Dice’s existing strong ties in academia. 

The research is being supported by Innovate UK, which is funding a series of research and development projects aimed at developing a commercially ready QRNG for various applications as well as developing internationally recognized hardware standards for QRNGs.

References and Further Reading

Leonhardt. U. (2010) Essential Quantum Optics: From Quantum Measurements to Black Holes. Cambridge: Cambridge University Presshttps://doi.org/10.1017/CBO9780511806117  

Isaac. [Online] Radioactive Decay. Available at: https://isaacphysics.org/concepts/cp_radioactive_decay?stage=all

Hart. A. (2021) What is radiometric dating? [Online] Cosmos Magazine. Available at: https://cosmosmagazine.com/earth/earth-sciences/what-is-radiometric-dating/

Sonnerup. J. (2019) On the Difficulty of Generating Random Numbers [Online] Debricked. Available at: https://debricked.com/blog/difficulty-of-generating-random-numbers/

Random Number Generator, Security Encyclopedia.

Disclaimer: The views expressed here are those of the author expressed in their private capacity and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork the owner and operator of this website. This disclaimer forms part of the Terms and conditions of use of this website.

Robert Lea

Written by

Robert Lea

Robert is a Freelance Science Journalist with a STEM BSc. He specializes in Physics, Space, Astronomy, Astrophysics, Quantum Physics, and SciComm. Robert is an ABSW member, and aWCSJ 2019 and IOP Fellow.


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