Ensuring Quality of Random Numbers from TRNG: Design and Evaluation of Post-Processing Using Genetic Algorithm

作     者：Jose J. Mijares Chan Parimala Thulasiraman Gabriel Thomas Ruppa Thulasiram Jose J. Mijares Chan;Parimala Thulasiraman;Gabriel Thomas;Ruppa Thulasiram

作者机构：Electrical and Computer Engineering Department-Faculty of Engineering University of Manitoba Winnipeg Canada Computer Science Department Faculty of Science University of Manitoba Winnipeg Canada 

出 版 物：《Journal of Computer and Communications》 (电脑和通信（英文）)

年 卷 期：2016年第4卷第4期

页      码：73-92页

摘      要：Random numbers generated by pseudo-random and true random number generators (TRNG) are used in a wide variety of important applications. A TRNG relies on a non-deterministic source to sample random numbers. In this paper, we improve the post-processing stage of TRNGs using a heuristic evolutionary algorithm. Our post-processing algorithm decomposes the problem of improving the quality of random numbers into two phases: (i) Exact Histogram Equalization: it modifies the random numbers distribution with a specified output distribution;(ii) Stationarity Enforcement: using genetic algorithms, the output of (ii) is permuted until the random numbers meet wide-sense stationarity. We ensure that the quality of the numbers generated from the genetic algorithm is within a specified level of error defined by the user. We parallelize the genetic algorithm for improved performance. The post-processing is based on the power spectral density of the generated numbers used as a metric. We propose guideline parameters for the evolutionary algorithm to ensure fast convergence, within the first 100 generations, with a standard deviation over the specified quality level of less than 0.45. We also include a TestU01 evaluation over the random numbers generated.

主 题 词：True Random Number Generators Genetic Algorithms Auto-Correlation Entropy Power Spectral Density 

学科分类：08[工学] 0812[工学-测绘类] 

D　O　I：10.4236/jcc.2016.44007

馆 藏 号：203459984...