This QRNG can be used in multiple applications across different sectors such as Finance, Industry, Telco or Research and in multiple Use Cases: Metaverse, Cryptography, Automotive, Scientific modeling, Gaming
Benefits of Quantum Random Numbers vs. Classic
- Most of Classic RNGs are Pseudo Random Number Generators (PRNG)
- The source of randomness is unpredictable and controlled by quantum process.
- The entropy source tends to produce true random output.
- Live/ real-time monitoring of entropy source is possible and highly effective as well.
- All attacks on the entropy source are detectable.
Quantum Random Numbers for the Metaverse
There are multiple use cases in the Metaverse where Quantum Random Numbers can be applied. These are some of them where the fully non-deterministic nature of Quantum Randomness provides a great advantage:
- Blockchain gaming
- NFT collections
- DeFi Protocols
- Custodial and Non-Custodial Draws
- Randomizing Rebase Times
- Marketing Campaigns and Loyalty Rewards
- Fair Selection and Ordering Processes
- Authentication and Security
Quantum Random Numbers for Security and Cryptography
Random numbers are important in computing. TCP/IP sequence numbers, TLS nonces, ASLR offsets, password salts, and DNS source port numbers all rely on random numbers. In cryptography randomness is found everywhere, from the generation of keys to encryption systems.
Some applications where the QRNG can be applied are:
- Secure wireless communications, including 802.11i, 802.15.3, 802.15.4 (ZigBee), MBOA, 802.16e
- Electronic financial transactions
- Content protection, digital rights management (DRM), set-top boxes
- Secure RFID
- Secure Smart Cards
Automotive (V2X, CAN, Infotainment, etc)
Detailed simulation models have to incorporate random effects. Since the generation of randomness is subject to several shortcomings, this needs to be considered for the selection of the randomness generator.
Random sequences are necessary for the domain of V2X (Vehicle-to-everything). It is important to avoid skewed results caused by classic or pseudo random number generation and ensure the statistical relevance of the simulation series.
Artificial Intelligence (Machine and Deep Learning)
Quantum Randomness can be used as a tool in preparing data and in learning algorithms that map input data to output data in order to make predictions. It is used to help the learning algorithms be more robust and ultimately result in better predictions and more accurate models.
Scientific Modeling & Simulations
A QRNG can be used to help the learning algorithms be more robust and ultimately result in better predictions and more accurate models.
Random number generators are continuously used for more and more gaming functions and algorithms. Quantum randomness allows you to make your games less ‘determined’ and thus more difficult for the player to beat, which means less patterns and more potential for replay.
- Easy-to-use SaaS endpoint
- Request from 32 bits to 1MB of random data per request
- Online service based on True Random Numuber Generators that relay on hardware components using Photonic Integrated Chips (PICs).