1 Let us finally present the pseudorandom number generator $\chi_{\textit{15Rairo}}$
2 which is based on random walks in $\Gamma(f)$.
3 More precisely, let be given a Boolean map $f:\Bool^n \rightarrow \Bool^n$,
4 a PRNG \textit{Random},
5 an integer $b$ that corresponds an iteration number (\textit{i.e.}, the length of the walk), and
6 an initial configuration $x^0$.
7 Starting from $x^0$, the algorithm repeats $b$ times
8 a random choice of which edge to follow and traverses this edge
9 provided it is allowed to traverse it, \textit{i.e.},
10 when $\textit{Random}(1)$ is not null.
11 The final configuration is thus outputted.
12 This PRNG is formalized in Algorithm~\ref{CI Algorithm}.
18 \KwIn{a function $f$, an iteration number $b$, an initial configuration $x^0$ ($n$ bits)}
19 \KwOut{a configuration $x$ ($n$ bits)}
23 \If{$\textit{Random}(1) \neq 0$}{
24 $s\leftarrow{\textit{Random}(n)}$\;
25 $x\leftarrow{F_f(s,x)}$\;
30 \caption{Pseudo Code of the $\chi_{\textit{15Rairo}}$ PRNG}
35 This PRNG is a particularized version of Algorithm given in~\cite{DBLP:conf/secrypt/CouchotHGWB14}.
36 As this latter, the length of the random
37 walk of our algorithm is always constant (and is equal to $b$).
38 However, in the current version, we add the constraint that
39 the probability to execute the function $F_f$ is equal to 0.5 since
40 the output of $\textit{Random(1)}$ is uniform in $\{0,1\}$.
42 Let $f: \Bool^{n} \rightarrow \Bool^{n}$.
43 It has been shown~\cite[Th. 4, p. 135]{BCGR11}} that
44 if its iteration graph is strongly connected, then
45 the output of $\chi_{\textit{14Secrypt}}$ follows
46 a law that tends to the uniform distribution
47 if and only if its Markov matrix is a doubly stochastic matrix.
49 Let us now present a method to
51 with Doubly Stochastic matrix and Strongly Connected iteration graph,
52 denoted as DSSC matrix.