True random number generators secure in a changing environment

Boaz Barak, Ronen Shaltiel, Eran Tromer

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

A true random number generator (TRNG) usually consists of two components: an "unpredictable" source with high entropy, and a randomness extractor - a function which, when applied to the source, produces a result that is statistically close to the uniform distribution. When the output of a TRNG is used for cryptographic needs, it is prudent to assume that an adversary may have some (limited) influence on the distribution of the high-entropy source. In this work: 1. We define a mathematical model for the adversary's influence on the source. 2. We show a simple and efficient randomness extractor and prove that it works for all sources of sufficiently high-entropy, even if individual bits in the source are correlated. 3. Security is guaranteed even if an adversary has (bounded) influence on the source. Our approach is based on a related notion of "randomness extraction" which emerged in complexity theory. We stress that the statistical randomness of our extractor's output is proven, and is not based on any unproven assumptions, such as the security of cryptographic hash functions. A sample implementation of our extractor and additional details can be found at a dedicated web page [Web].

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsColin D. Walter, Cetin K. Koc, Christof Paar
PublisherSpringer Verlag
Pages166-180
Number of pages15
ISBN (Print)3540408339, 9783540408338
DOIs
StatePublished - 2003
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2779
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Fingerprint

Dive into the research topics of 'True random number generators secure in a changing environment'. Together they form a unique fingerprint.

Cite this