X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/prng_gpu.git/blobdiff_plain/14b55657fe448a88441d16d87e11398351dfb4ab..b21f8a014461c2e21ea80c2620286f1fe4c8dec2:/prng_gpu.tex?ds=inline diff --git a/prng_gpu.tex b/prng_gpu.tex index 807f6df..3c6e281 100644 --- a/prng_gpu.tex +++ b/prng_gpu.tex @@ -1,6 +1,6 @@ -%\documentclass{article} +\documentclass{article} %\documentclass[10pt,journal,letterpaper,compsoc]{IEEEtran} -\documentclass[preprint,12pt]{elsarticle} +%\documentclass[preprint,12pt]{elsarticle} \usepackage[utf8]{inputenc} \usepackage[T1]{fontenc} \usepackage{fullpage} @@ -40,15 +40,28 @@ \newcommand{\alert}[1]{\begin{color}{blue}\textit{#1}\end{color}} - +\begin{document} \title{Efficient and Cryptographically Secure Generation of Chaotic Pseudorandom Numbers on GPU} -\begin{document} -\author{Jacques M. Bahi, Rapha\"{e}l Couturier, Christophe -Guyeux, and Pierre-Cyrille Héam*\\ FEMTO-ST Institute, UMR 6174 CNRS,\\ University of Franche-Comt\'{e}, Besan\c con, France\\ * Authors in alphabetic order} - +%% \author{Jacques M. Bahi} +%% \ead{jacques.bahi@univ-fcomte.fr} +%% \author{ Rapha\"{e}l Couturier \corref{cor1}} +%% \ead{raphael.couturier@univ-fcomte.fr} +%% \cortext[cor1]{Corresponding author} +%% \author{ Christophe Guyeux} +%% \ead{christophe.guyeux@univ-fcomte.fr} +%% \author{ Pierre-Cyrille Héam } +%% \ead{pierre-cyrille.heam@univ-fcomte.fr} + +\author{Christophe Guyeux \and Rapha\"{e}l Couturier \and Pierre-Cyrille Héam \and Jacques M. Bahi\\ +FEMTO-ST Institute, UMR 6174 CNRS,\\ University of Franche Comte, Belfort, France} + +\maketitle + + +%\begin{frontmatter} %\IEEEcompsoctitleabstractindextext{ \begin{abstract} In this paper we present a new pseudorandom number generator (PRNG) on @@ -65,8 +78,11 @@ A chaotic version of the Blum-Goldwasser asymmetric key encryption scheme is fin \end{abstract} %} +%\begin{keyword} +% pseudo random number\sep parallelization\sep GPU\sep cryptography\sep chaos +%\end{keyword} +%\end{frontmatter} -\maketitle %\IEEEdisplaynotcompsoctitleabstractindextext %\IEEEpeerreviewmaketitle @@ -177,8 +193,8 @@ Pseudorandom numbers are generated at a rate of 20GSamples/s, which is faster than in~\cite{conf/fpga/ThomasHL09,Marsaglia2003} (and with a better statistical behavior). Experiments are also provided using BBS as the initial random generator. The generation speed is significantly weaker. -Note also that an original qualitative comparison between topological chaotic -properties and statistical tests is also proposed. +%Note also that an original qualitative comparison between topological chaotic +%properties and statistical tests is also proposed. @@ -1786,14 +1802,7 @@ Let $\varepsilon > 0$. $\mathcal{D}$ is called a $(T,\varepsilon)-$distinguishing attack on pseudorandom generator $G$ if -\begin{flushleft} -$\left| Pr[\mathcal{D}(G(k)) = 1 \mid k \in_R \{0,1\}^\ell ]\right.$ -\end{flushleft} - -\begin{flushright} -$ - \left. Pr[\mathcal{D}(s) = 1 \mid s \in_R \mathds{B}^M ]\right| \geqslant \varepsilon,$ -\end{flushright} - +$$\left| Pr[\mathcal{D}(G(k)) = 1 \mid k \in_R \{0,1\}^\ell ]\right. - \left. Pr[\mathcal{D}(s) = 1 \mid s \in_R \mathds{B}^M ]\right| \geqslant \varepsilon,$$ \noindent where the probability is taken over the internal coin flips of $\mathcal{D}$, and the notation ``$\in_R$'' indicates the process of selecting an element at random and uniformly over the corresponding set.