2024 · 10 citations · 21 references
ComputingComputer ScienceCybersecurityComputer SecurityCryptographyQuantum ComputingQuantum BitsQuantum CircuitsQuantum CryptographyRandom Number GenerationBoolean EquationsCorrelationCryptographic Random Number GenerationQuantum EntropyQuantum Random Number GenerationRandom Sequence GenerationRandomness ExtractionTrue Random Number Generation
Random numbers play a central role in cryptography, cyber security, and gaming applications. Extracting bits from some random natural activity is one of the primitive ways to generate random numbers. True random number generator(TRNG) and quantum random number generator(QRNG) are examples of this random number sequence. The development of quantum technology made it possible to extract random sequences from quantum entropy sources. This sequence is called quantum random numbers and the whole setup is named a quantum random number generator. A suitable sampling and a physical device for the entropy source are the building blocks for a TRNG. Here we present a comparative analysis of two random number generators. Apart from the conventional statistical test for randomness, here we introduce a straightforward coefficient based on the concept of non-linearity of the Boolean function to determine the availability of any linearity in a chosen random binary sequence. It reveals the cryptographic suitability of the generated sequence w.r.t any correlation attack. A comparison of the nonlinearity of two Boolean sequences generated from two different random sources is presented.
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O. S. Rothaus · Journal of Combinatorial Theory Series A · 1976 · 1.3K citations
Quantum random number generation
Xiongfeng Ma, Xiao Yuan, Zhu Cao et al. · npj Quantum Information · 2016 · 424 citations · Full text
Computing, Computer Science, Physics +11
A. N. Kolmogorov · Theoretical Computer Science · 1998 · 376 citations