True Randomness from Big Data

doi:10.1038/srep33740

	True Randomness from Big Data
	Papakonstantinou, Periklis A.1; Woodruff, David P.2; Yang, Guang 3
	2016-09-26
发表期刊	SCIENTIFIC REPORTS
ISSN	2045-2322
卷号	6 页码:8
摘要	Generating random bits is a difficult task, which is important for physical systems simulation, cryptography, and many applications that rely on high-quality random bits. Our contribution is to show how to generate provably random bits from uncertain events whose outcomes are routinely recorded in the form of massive data sets. These include scientific data sets, such as in astronomics, genomics, as well as data produced by individuals, such as internet search logs, sensor networks, and social network feeds. We view the generation of such data as the sampling process from a big source, which is a random variable of size at least a few gigabytes. Our view initiates the study of big sources in the randomness extraction literature. Previous approaches for big sources rely on statistical assumptions about the samples. We introduce a general method that provably extracts almost-uniform random bits from big sources and extensively validate it empirically on real data sets. The experimental findings indicate that our method is efficient enough to handle large enough sources, while previous extractor constructions are not efficient enough to be practical. Quality-wise, our method at least matches quantum randomness expanders and classical world empirical extractors as measured by standardized tests.
DOI	10.1038/srep33740
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61222202] ; National Natural Science Foundation of China[61433014] ; National Natural Science Foundation of China[61502449] ; National Natural Science Foundation of China[61602440] ; China National Program
WOS研究方向	Science & Technology - Other Topics
WOS类目	Multidisciplinary Sciences
WOS记录号	WOS:000384416200001
出版者	NATURE PUBLISHING GROUP
引用统计	被引频次：5[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/8141
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Woodruff, David P.
作者单位	1.Rutgers State Univ, MSIS, Piscataway, NJ 08853 USA 2.IBM Res Almaden, San Jose, CA 95120 USA 3.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Papakonstantinou, Periklis A.,Woodruff, David P.,Yang, Guang. True Randomness from Big Data[J]. SCIENTIFIC REPORTS,2016,6:8.
APA	Papakonstantinou, Periklis A.,Woodruff, David P.,&Yang, Guang.(2016).True Randomness from Big Data.SCIENTIFIC REPORTS,6,8.
MLA	Papakonstantinou, Periklis A.,et al."True Randomness from Big Data".SCIENTIFIC REPORTS 6(2016):8.