Abstract
We present a true random number generator (TRNG) using dark noise of a CMOS image sensor. Because the proposed TRNG is based on the dark characteristics of the CMOS image sensor, it does not require any additional hardware, such as light source and optics, for providing true randomness. Therefore, it can be a promising solution for compact and low-cost mobile application. By using NIST SP 800-90B entropy assessment suite, we evaluate the min-entropy for the raw outputs of our original noise source and the final random numbers including post-processing as well. We also adopt NIST SP 800-22 statistical randomness test suite for the evaluation of the random numbers. The test results demonstrate that the generated random numbers pass all the statistical tests and have high entropy.
Highlights
Random number generators (RNGs) are extensively used in several traditional fields such as simulation, gaming, cryptography [1]–[3], etc
Several research groups have been focusing on the quantum random number generator (QRNG) considered to be a promising solution for the true random number generator (TRNG) owing to its inherently unpredictable quantum phenomena
Note that NIST SP 800-22 is a statistical test suite for random and pseudorandom number sequence, and NIST SP 800-90B is an entropy estimation method to validate the quality of the entropy source, which is an output of non-deterministic process
Summary
Random number generators (RNGs) are extensively used in several traditional fields such as simulation, gaming, cryptography [1]–[3], etc. In simulation and gaming, the pseudo random number generator (PRNG) has generated attention owing to superior characteristics such as a high bit rate, unbiased output, cost-effectiveness, and easy implementation. A physical random number generator, which utilizes the chaotic behavior of physical processes including thermal noise [4], chaotic lasers [5], circuit noise [6]–[8], optical noise [9], [10], and air disturbances [11], is adopted in cryptography that require high quality of randomness.
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