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True Random Number Generators

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Abstract

Random numbers are needed in many areas: cryptography, Monte Carlo computation and simulation, industrial testing and labeling, hazard games, gambling, etc. Our assumption has been that random numbers cannot be computed; because digital computers operate deterministically, they cannot produce random numbers. Instead, random numbers are best obtained using physical (true) random number generators (TRNG), which operate by measuring a well-controlled and specially prepared physical process. Randomness of a TRNG can be precisely, scientifically characterized and measured. Especially valuable are the information-theoretic provable random number generators (RNGs), which, at the state of the art, seem to be possible only by exploiting randomness inherent to certain quantum systems. On the other hand, current industry standards dictate the use of RNGs based on free-running oscillators (FRO) whose randomness is derived from electronic noise present in logic circuits and which cannot be strictly proven as uniformly random, but offer easier technological realization. The FRO approach is currently used in 3rd- and 4th-generation FPGA and ASIC hardware, unsuitable for realization of quantum RNGs. In this chapter we compare weak and strong aspects of the two approaches. Finally, we discuss several examples where use of a true RNG is critical and show how it can significantly improve security of cryptographic systems, and discuss industrial and research challenges that prevent widespread use of TRNGs.

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  1. Centre of Excellence for Advanced Materials and Sensors, Rudjer Bošković Institute, Zagreb, Croatia

    Mario Stipčević

  2. University of California Santa Barbara, Santa Barbara, CA, 93106, USA

    Mario Stipčević & Çetin Kaya Koç

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  1. Mario Stipčević
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  1. Dept. of Computer Science, University of California, Santa Barbara, Santa Barbara, California, USA

    Çetin Kaya Koç

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Stipčević, M., Koç, Ç.K. (2014). True Random Number Generators. In: Koç, Ç. (eds) Open Problems in Mathematics and Computational Science. Springer, Cham. https://doi.org/10.1007/978-3-319-10683-0_12

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