1 Let us finally present the pseudorandom number generator $\chi_{\textit{15Rairo}}$,
2 which is based on random walks in $\Gamma_{\{b\}}(f)$.
3 More precisely, let be given a Boolean map $f:\Bool^{\mathsf{N}} \rightarrow
5 a PRNG \textit{Random},
6 an integer $b$ that corresponds to an iteration number (\textit{i.e.}, the length of the walk), and
7 an initial configuration $x^0$.
8 Starting from $x^0$, the algorithm repeats $b$ times
9 a random choice of which edge to follow, and traverses this edge
10 provided it is allowed to do so, \textit{i.e.},
11 when $\textit{Random}(1)$ is not null.
12 The final configuration is thus outputted.
13 This PRNG is formalized in Algorithm~\ref{CI Algorithm:2}.
19 \KwIn{a function $f$, an iteration number $b$, an initial configuration $x^0$ ($n$ bits)}
20 \KwOut{a configuration $x$ ($n$ bits)}
24 \If{$\textit{Random}(1) \neq 0$}{
25 $s\leftarrow{\textit{Random}(n)}$\;
26 $x\leftarrow{F_f(s,x)}$\;
31 \caption{Pseudo Code of the $\chi_{\textit{15Rairo}}$ PRNG}
32 \label{CI Algorithm:2}
36 This PRNG is slightly different from $\chi_{\textit{14Secrypt}}$
37 recalled in Algorithm~\ref{CI Algorithm}.
38 As this latter, the length of the random
39 walk of our algorithm is always constant (and is equal to $b$).
40 However, in the current version, we add the constraint that
41 the probability to execute the function $F_f$ is equal to 0.5 since
42 the output of $\textit{Random(1)}$ is uniform in $\{0,1\}$.
43 This constraint is added to match the theoretical framework of
44 Sect.~\ref{sec:hypercube}.
48 Notice that the chaos property of $G_f$ given in Sect.\ref{sec:proofOfChaos}
49 only requires that the graph $\Gamma_{\{b\}}(f)$ is strongly connected.
50 Since the $\chi_{\textit{15Rairo}}$ algorithm
51 only adds probability constraints on existing edges,
52 it preserves this property.
55 For each number $\mathsf{N}=4,5,6,7,8$ of bits, we have generated
56 the functions according to the method
57 given in Sect.~\ref{sec:SCCfunc}.
58 % MENTION FILTRAGE POSSIBLE LORS DE CONSTRUCTION... (SCV)
59 For each $\mathsf{N}$, we have then restricted this evaluation to the function
60 whose Markov Matrix (issued from Eq.~(\ref{eq:Markov:rairo}))
61 has the smallest practical mixing time.
63 given in Table~\ref{table:nc}.
64 In this table, let us consider for instance
65 the function $\textcircled{a}$ from $\Bool^4$ to $\Bool^4$
66 defined by the following images :
67 $[13, 10, 9, 14, 3, 11, 1, 12, 15, 4, 7, 5, 2, 6, 0, 8]$.
68 In other words, the image of $3~(0011)$ by $\textcircled{a}$ is $14~(1110)$:
69 it is obtained as the binary value of the fourth element in
70 the second list (namely~14).
72 In this table the column
73 that is labeled with $b$ (respectively by $E[\tau]$)
74 gives the practical mixing time
75 where the deviation to the standard distribution is lesser than $10^{-6}$
76 (resp. the theoretical upper bound of stopping time as described in
77 Sect.~\ref{sec:hypercube}).
84 \begin{tabular}{|c|c|c|c|c|}
86 Function $f$ & $f(x)$, for $x$ in $(0,1,2,\hdots,2^n-1)$ & $\mathsf{N}$ & $b$
90 $\textcircled{a}$&[13,10,9,14,3,11,1,12,15,4,7,5,2,6,0,8]&4&64&154\\
94 [29, 22, 25, 30, 19, 27, 24, 16, 21, 6, 5, 28, 23, 26, 1, 17, & 5 & 78 & 236\\
96 31, 12, 15, 8, 10, 14, 13, 9, 3, 2, 7, 20, 11, 18, 0, 4]
101 [55, 60, 45, 44, 58, 62, 61, 48, 53, 50, 52, 36, 59, 34, 33, 49,
104 15, 42, 47, 46, 35, 10, 57, 56, 7, 54, 39, 37, 51, 2, 1, 40, 63,
107 26, 25, 30, 19, 27, 17, 28, 31, 20, 23, 21, 18, 22, 16, 24, 13,
110 12, 29, 8, 43, 14, 41, 0, 5, 38, 4, 6, 11, 3, 9, 32]
115 [111, 94, 93, 116, 122, 90, 125, 88, 115, 126, 119, 84, 123, 98,
118 81, 120, 109, 106, 105, 110, 99, 107, 104, 72, 71, 118, 117,
121 96, 103, 102, 113, 64, 79, 86, 95, 124, 83, 91, 121, 24, 85, 22,
124 69, 20, 19, 114, 17, 112, 77, 76, 13, 108, 74, 10, 9, 73, 67, 66,
128 101, 100, 75, 82, 97, 0, 127, 54, 57, 62, 51, 59, 56, 48, 53, 38,
131 37, 60, 55, 58, 33, 49, 63, 44, 47, 40, 42, 46, 45, 41, 35, 34,
134 39, 52, 43, 50, 32, 36, 29, 28, 61, 92, 26, 18, 89, 25, 87, 30,
137 23, 4, 27, 2, 16, 80, 31, 78, 15, 14, 3, 11, 8, 12, 5, 70, 21,
147 [223, 190, 249, 254, 187, 251, 233, 232, 183, 230, 247, 180, 227,
150 178, 240, 248, 237, 236, 253, 172, 203, 170, 201, 168, 229, 166,
153 165, 244, 163, 242, 241, 192, 215, 220, 205, 216, 218, 222, 221,
156 208, 213, 210, 212, 214, 219, 211, 217, 209, 239, 202, 207, 140,
159 139, 234, 193, 204, 135, 196, 199, 132, 194, 130, 225, 200, 159,
162 62, 185, 252, 59, 250, 169, 56, 191, 246, 245, 52, 243, 50, 176,
165 48, 173, 238, 189, 44, 235, 42, 137, 184, 231, 38, 37, 228, 35,
168 226, 177, 224, 151, 156, 141, 152, 154, 158, 157, 144, 149, 146,
171 148, 150, 155, 147, 153, 145, 175, 206, 143, 136, 11, 142, 129,
174 8, 7, 198, 197, 4, 195, 2, 161, 160, 255, 124, 109, 108, 122,
177 126, 125, 112, 117, 114, 116, 100, 123, 98, 97, 113, 79, 106,
180 111, 110, 99, 74, 121, 120, 71, 118, 103, 101, 115, 66, 65,
183 104, 127, 90, 89, 94, 83, 91, 81, 92, 95, 84, 87, 85, 82, 86,
186 80, 88, 77, 76, 93, 72, 107, 78, 105, 64, 69, 102, 68, 70, 75,
189 67, 73, 96, 55, 58, 45, 188, 51, 186, 61, 40, 119, 182, 181,
192 53, 179, 54, 33, 49, 15, 174, 47, 60, 171, 46, 57, 32, 167, 6,
195 36, 164, 43, 162, 1, 0, 63, 26, 25, 30, 19, 27, 17, 28, 31,
198 20, 23, 21, 18, 22, 16, 24, 13, 10, 29, 14, 3, 138, 41, 12,
201 39, 134, 133, 5, 131, 34, 9, 128]
207 \caption{Functions with DSCC Matrix and smallest MT\label{table:nc}}
212 Let us first discuss about results against the NIST test suite.
213 In our experiments, 100 sequences (s = 100) of 1,000,000 bits are generated and tested.
214 If the value $\mathbb{P}_T$ of any test is smaller than 0.0001, the sequences are considered to be not good enough
215 and the generator is unsuitable. Table~\ref{The passing rate} shows $\mathbb{P}_T$ of sequences based on discrete
216 chaotic iterations using different schemes. If there are at least two statistical values in a test, this test is
217 marked with an asterisk and the average value is computed to characterize the statistics.
218 We can see in Table \ref{The passing rate} that all the rates are greater than 97/100, \textit{i.e.}, all the generators
219 achieve to pass the NIST battery of tests.
224 \renewcommand{\arraystretch}{1.3}
227 \setlength{\tabcolsep}{2pt}
230 \begin{tabular}{|l|l|l|l|l|l|}
232 Method &$\textcircled{a}$& $\textcircled{b}$ & $\textcircled{c}$ & $\textcircled{d}$ & $\textcircled{e}$ \\ \hline\hline
233 Frequency (Monobit)& 0.851 (0.98)& 0.719 (0.99)& 0.699 (0.99)& 0.514 (1.0)& 0.798 (0.99)\\ \hline
234 Frequency (Monobit)& 0.851 (0.98)& 0.719 (0.99)& 0.699 (0.99)& 0.514 (1.0)& 0.798 (0.99)\\ \hline
235 Frequency within a Block& 0.262 (0.98)& 0.699 (0.98)& 0.867 (0.99)& 0.145 (1.0)& 0.455 (0.99)\\ \hline
236 Cumulative Sums (Cusum) *& 0.301 (0.98)& 0.521 (0.99)& 0.688 (0.99)& 0.888 (1.0)& 0.598 (1.0)\\ \hline
237 Runs& 0.224 (0.97)& 0.383 (0.97)& 0.108 (0.96)& 0.213 (0.99)& 0.616 (0.99)\\ \hline
238 Longest Run of 1s & 0.383 (1.0)& 0.474 (1.0)& 0.983 (0.99)& 0.699 (0.98)& 0.897 (0.96)\\ \hline
239 Binary Matrix Rank& 0.213 (1.0)& 0.867 (0.99)& 0.494 (0.98)& 0.162 (0.99)& 0.924 (0.99)\\ \hline
240 Disc. Fourier Transf. (Spect.)& 0.474 (1.0)& 0.739 (0.99)& 0.012 (1.0)& 0.678 (0.98)& 0.437 (0.99)\\ \hline
241 Unoverlapping Templ. Match.*& 0.505 (0.990)& 0.521 (0.990)& 0.510 (0.989)& 0.511 (0.990)& 0.499 (0.990)\\ \hline
242 Overlapping Temp. Match.& 0.574 (0.98)& 0.304 (0.99)& 0.437 (0.97)& 0.759 (0.98)& 0.275 (0.99)\\ \hline
243 Maurer's Universal Statistical& 0.759 (0.96)& 0.699 (0.97)& 0.191 (0.98)& 0.699 (1.0)& 0.798 (0.97)\\ \hline
244 Approximate Entropy (m=10)& 0.759 (0.99)& 0.162 (0.99)& 0.867 (0.99)& 0.534 (1.0)& 0.616 (0.99)\\ \hline
245 Random Excursions *& 0.666 (0.994)& 0.410 (0.962)& 0.287 (0.998)& 0.365 (0.994)& 0.480 (0.985)\\ \hline
246 Random Excursions Variant *& 0.337 (0.988)& 0.519 (0.984)& 0.549 (0.994)& 0.225 (0.995)& 0.533 (0.993)\\ \hline
247 Serial* (m=10)& 0.630 (0.99)& 0.529 (0.99)& 0.460 (0.99)& 0.302 (0.995)& 0.360 (0.985)\\ \hline
248 Linear Complexity& 0.719 (1.0)& 0.739 (0.99)& 0.759 (0.98)& 0.122 (0.97)& 0.514 (0.99)\\ \hline
252 \caption{NIST SP 800-22 test results ($\mathbb{P}_T$)}
253 \label{The passing rate}
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