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Probability distributions for the Linux entropy estimator. (English) Zbl 1431.65009
Summary: We propose a mathematical model of the entropy estimator in the Linux random number generator. First, we construct a probability model for random event times in entropy sources, and then precisely derive probability distributions for the first, second, and third time differences. Second, we obtain the probability distribution for the minimum of absolute values of these differences, which is used for the estimated entropy in the Linux system. Moreover, we provide several simulations that display the accuracy of our results for various parameters.
65C10 Random number generation in numerical analysis
94A17 Measures of information, entropy
Full Text: DOI
[1] National Institute of Standards and Technology, NIST Draft Special Publication 800-90B, Recommendation for the Entropy Sources Used for Random Bit Genreration, 2016, http://csrc.nist.gov/publications/drafts/800-90/draft-sp800-90b.pdf.
[2] CC, The common criteria for information technology security evaluation. http://www.commoncriteriapotal.org/.
[3] CMVP, Cryptographic module validation program. http://http://csrc.nist.gov/groups/STM/cmvp/.
[4] Dodis, Y.; Pointcheval, D.; Ruhault, S.; Vergniaud, D.; Wichs, D., Security analysis of pseudo-random number generators with input:/dev/random is not robust, (Proceedings of the 2013 ACM SIGSAC Conference on Computer & Communications Security, (2013), ACM), 647-658
[5] Gutterman, Z.; Pinkas, B.; Reinman, T., Analysis of the Linux random number generator, (2006 IEEE Symposium on Security and Privacy, (2006), IEEE), 371-385
[6] ISO/IEC 3rd WD 20543, Information technology - Security techniques - Test and analysis methods for random bit generators within ISO/IEC 19790 and ISO/IEC 15408, 2016.
[7] J. Kelsey, Entropy and entropy sources in x9.82, in: Proceeding of the NIST Random Number Generation Workshop, 2004.
[8] Kim, S. H.; Han, D.; Lee, D. H., Predictability of android openssl’s pseudo random number generator, (Proceedings of the 2013 ACM SIGSAC Conference on Computer & Communications Security, (2013), ACM), 659-668
[9] Lacharme, P.; Röck, A.; Strubel, V.; Videau, M., The Linux pseudorandom number generator revisited, cryptology eprint archive, report 2012/251, (2012)
[10] Linux, The linux kernel archives. http://www.kernel.org/.
[11] FIPS PUB 140-2: security requirements for cryptographic modules, 15, (2001), National Institute of Standards and Technology
[12] Pousse, B., Short communication: an interpretation of the Linux entropy estimator, cryptology eprint archive, report 2012/487, (2012)
[13] Schindler, W., Efficient online tests for true random number generators, (Cryptographic Hardware and Embedded Systems, CHES 2001, (2001), Springer), 103-117 · Zbl 1006.68704
[14] Vuillemin, T.; Goichon, F.; Lauradoux, C.; Salagnac, G., Entropy transfers in the Linux random number generator, research report 8060, INRIA, (2012)
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