Random number generation is one of the unsung heroes of many industries, critical for ensuring security, safety, and fairness of use. What actually is it, and what do new innovations signal for the future? Let’s take a look.
What is random number generation?
Random number generation is the process of generating random numbers using a random number generator (RNG). RNGs can be leveraged in a wide range of applications – from cryptography to internet security, theoretical research, and even in entertainment. Take online casinos, for example. In a brick-and-mortar casino, players roll a dice, flip a coin, spin a wheel, or a dealer shuffles the cards for their hand. To mirror this element of chance, an online casino might use an RNG instead for the same purpose, which selects cards, winning symbols, the placement of a roulette ball, and bingo calls to preserve the fairness and authenticity of the games offered.
There are two main types of RNGs: true random number generation (TRNG), which typically utilizes hardware random number generators (HRNGs), and pseudorandom number generators (PRNGs). Put simply, HRNGs function in a constantly changing environment, which is nigh-on impossible to calculate. On the other hand, PRNG sequences are generated using a specific function, and so merely appear as random. That said, both HRNGs and PRNGs are tested against a standard of statistical randomness before being deployed to ensure they are unpredictable enough for their intended usage.
Now that you know the basics of what RNGs are, let’s take a look at some innovative technological developments in the industry.
New era of RNGs
As we mentioned, PRNG sequences may appear random, but are actually pre-determined. Though some cryptographic PRNGs do exist, PRNGs are largely considered unsuitable for this purpose. That said, TRNG can be extremely difficult, as randomness cannot truly be captured by a mathematical formula. That’s what a group of researchers with King Abdullah University of Science and Technology aimed to solve, announcing a TRNG made from a printable electronic circuit that has been hailed by some as the key to cryptography.
Source: Pixabay
The circuit is inkjet printed using a technique called memristors. The first of its kind, the memristor fabrication holds similarities to 3D printing, and creates TRNGs that have lower energy consumption and higher stability than its predecessors, generating 7 million random bits per second, which could be revolutionary for complex micro- and nanoelectronics.
Others, however, have taken another approach to RNG technology, integrating it with the advancements in quantum computing. Put simply, quantum computing leverages the rules of quantum mechanics to solve more complex calculations more quickly and efficiently. Whilst in traditional computing, numbers have to be either 0 or 1, in quantum computing they could be 0 and 1 simultaneously.
This has led to a new range of RNGs – quantum random number generators (QRNGs). QRNGs leverage the multiplicity and indeterminacy of quantum mechanics in an attempt to generate numbers that are authentically random, using single-photon detection technology and entangled photons. That said, if an input source had any error, this could eliminate randomness completely, hence a movement towards source-device-independent QRNGs which have been proposed to have been tested and ready for practical quantum security applications in the future.
As you can see, modern technological developments are consistently pushing RNGs to new heights, challenging the protocols to be as random as possible. These techniques and innovations have the potential to transform RNGs, their consistency, sustainability, and accuracy going forward.
