inria-00604857, version 2
Online Entropy Estimation for Non-Binary Sources and Applications on iPhone
Cédric Lauradoux
a, 1Julien Ponge b, 2Andrea Roeck c, 3
N° RR-7663 (2011)
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.
- a – INRIA
- b – INSA Lyon
- c – Aalto University School of Science, Department of Information and Computer Science
- 1: SWING (CITI Insa Lyon / INRIA Grenoble Rhône-Alpes)
- INRIA – Institut National des Sciences Appliquées de Lyon
- 2: AMAZONES (CITI Insa Lyon / Inria Grenoble Rhône-Alpes)
- INRIA – Institut National des Sciences Appliquées de Lyon
- 3: Department of Information and Computer Science
- Aalto University
- Domain : Computer Science/Cryptography and Security
- Keywords : Random number generator – online entropy estimation – iPhone – random sources.
- Internal note : RR-7663
- Available versions : v1 (2011-06-30) v2 (2011-07-18)
- inria-00604857, version 2
- http://hal.inria.fr/inria-00604857
- oai:hal.inria.fr:inria-00604857
- From: Cédric Lauradoux
- Submitted on: Monday, 18 July 2011 09:16:58
- Updated on: Monday, 18 July 2011 09:28:42
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