Abstract
Algorithmic post-processing is used to overcome statistical deficiencies of physical random number generators. We show that the quasigroup based approach for post-processing random numbers described in [MGK05] is ineffective and very easy to attack. We also suggest new algorithms which extract considerably more entropy from their input than the known algorithms with an upper bound for the number of input bits needed before the next output is produced. © International Association for Cryptologic Research 2007.
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CITATION STYLE
Dichtl, M. (2007). Bad and good ways of post-processing biased physical random numbers. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4593 LNCS, pp. 137–152). Springer Verlag. https://doi.org/10.1007/978-3-540-74619-5_9
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