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Online Entropy Estimation for Non-Binary Sources and Applications on iPhone
Abstract : The design of a random number generator is a challenging task on systems in changing environment such as smartphones. Finding reliable and high-throughput sources of entropy is difficult. This paper proposes an online entropy estimation algorithm to test the quality of an entropy source when nothing is known \textit{a priori} on the source statistics. Our estimator can be executed at a low cost and is adapted for any type of sources. It extends the results of Bucci and Luzzi to non-binary sources and introduces a parameter that allows to trade time and memory for a better estimate. Our estimator is then applied to several sources available on an iPhone and compare to the state of the art.
Cited literature [32 references]
https://hal.inria.fr/inria-00604857
Contributor : Cédric Lauradoux <>
Submitted on : Monday, July 18, 2011 - 9:16:58 AM
Last modification on : Thursday, November 26, 2020 - 2:56:03 PM
Long-term archiving on: : Sunday, December 4, 2016 - 10:43:49 AM
Contributor : Cédric Lauradoux <>
Submitted on : Monday, July 18, 2011 - 9:16:58 AM
Last modification on : Thursday, November 26, 2020 - 2:56:03 PM
Long-term archiving on: : Sunday, December 4, 2016 - 10:43:49 AM
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RR-7663.pdf
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