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Pollard's rho algorithm for logarithms

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Mathematical algorithm

Pollard's rho algorithm for logarithms is an algorithm introduced by John Pollard in 1978 to solve the discrete logarithm problem, analogous to Pollard's rho algorithm to solve the integer factorization problem.

The goal is to compute γ {\displaystyle \gamma } {\displaystyle \gamma } such that α γ = β {\displaystyle \alpha ^{\gamma }=\beta } {\displaystyle \alpha ^{\gamma }=\beta }, where β {\displaystyle \beta } {\displaystyle \beta } belongs to a cyclic group G {\displaystyle G} {\displaystyle G} generated by α {\displaystyle \alpha } {\displaystyle \alpha }. The algorithm computes integers a {\displaystyle a} {\displaystyle a}, b {\displaystyle b} {\displaystyle b}, A {\displaystyle A} {\displaystyle A}, and B {\displaystyle B} {\displaystyle B} such that α a β b = α A β B {\displaystyle \alpha ^{a}\beta ^{b}=\alpha ^{A}\beta ^{B}} {\displaystyle \alpha ^{a}\beta ^{b}=\alpha ^{A}\beta ^{B}}. If the underlying group is cyclic of order n {\displaystyle n} {\displaystyle n}, by substituting β {\displaystyle \beta } {\displaystyle \beta } as α γ {\displaystyle {\alpha }^{\gamma }} {\displaystyle {\alpha }^{\gamma }} and noting that two powers are equal if and only if the exponents are equivalent modulo the order of the base, in this case modulo n {\displaystyle n} {\displaystyle n}, we get that γ {\displaystyle \gamma } {\displaystyle \gamma } is one of the solutions of the equation ( B b ) γ = ( a A ) ( mod n ) {\displaystyle (B-b)\gamma =(a-A){\pmod {n}}} {\displaystyle (B-b)\gamma =(a-A){\pmod {n}}}. Solutions to this equation are easily obtained using the extended Euclidean algorithm.

To find the needed a {\displaystyle a} {\displaystyle a}, b {\displaystyle b} {\displaystyle b}, A {\displaystyle A} {\displaystyle A}, and B {\displaystyle B} {\displaystyle B} the algorithm uses Floyd's cycle-finding algorithm to find a cycle in the sequence x i = α a i β b i {\displaystyle x_{i}=\alpha ^{a_{i}}\beta ^{b_{i}}} {\displaystyle x_{i}=\alpha ^{a_{i}}\beta ^{b_{i}}}, where the function f : x i x i + 1 {\displaystyle f:x_{i}\mapsto x_{i+1}} {\displaystyle f:x_{i}\mapsto x_{i+1}} is assumed to be random-looking and thus is likely to enter into a loop of approximate length π n 8 {\displaystyle {\sqrt {\frac {\pi n}{8}}}} {\displaystyle {\sqrt {\frac {\pi n}{8}}}} after π n 8 {\displaystyle {\sqrt {\frac {\pi n}{8}}}} {\displaystyle {\sqrt {\frac {\pi n}{8}}}} steps. One way to define such a function is to use the following rules: Partition G {\displaystyle G} {\displaystyle G} into three disjoint subsets S 0 {\displaystyle S_{0}} {\displaystyle S_{0}}, S 1 {\displaystyle S_{1}} {\displaystyle S_{1}}, and S 2 {\displaystyle S_{2}} {\displaystyle S_{2}} of approximately equal size using a hash function. If x i {\displaystyle x_{i}} {\displaystyle x_{i}} is in S 0 {\displaystyle S_{0}} {\displaystyle S_{0}} then double both a {\displaystyle a} {\displaystyle a} and b {\displaystyle b} {\displaystyle b}; if x i S 1 {\displaystyle x_{i}\in S_{1}} {\displaystyle x_{i}\in S_{1}} then increment a {\displaystyle a} {\displaystyle a}, if x i S 2 {\displaystyle x_{i}\in S_{2}} {\displaystyle x_{i}\in S_{2}} then increment b {\displaystyle b} {\displaystyle b}.

Algorithm

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Let G {\displaystyle G} {\displaystyle G} be a cyclic group of order n {\displaystyle n} {\displaystyle n}, and given α , β G {\displaystyle \alpha ,\beta \in G} {\displaystyle \alpha ,\beta \in G}, and a partition G = S 0 S 1 S 2 {\displaystyle G=S_{0}\cup S_{1}\cup S_{2}} {\displaystyle G=S_{0}\cup S_{1}\cup S_{2}}, let f : G G {\displaystyle f:G\to G} {\displaystyle f:G\to G} be the map

f ( x ) = { β x x S 0 x 2 x S 1 α x x S 2 {\displaystyle f(x)={\begin{cases}\beta x&x\in S_{0}\\x^{2}&x\in S_{1}\\\alpha x&x\in S_{2}\end{cases}}} {\displaystyle f(x)={\begin{cases}\beta x&x\in S_{0}\\x^{2}&x\in S_{1}\\\alpha x&x\in S_{2}\end{cases}}}

and define maps g : G × Z Z {\displaystyle g:G\times \mathbb {Z} \to \mathbb {Z} } {\displaystyle g:G\times \mathbb {Z} \to \mathbb {Z} } and h : G × Z Z {\displaystyle h:G\times \mathbb {Z} \to \mathbb {Z} } {\displaystyle h:G\times \mathbb {Z} \to \mathbb {Z} } by

g ( x , k ) = { k x S 0 2 k ( mod n ) x S 1 k + 1 ( mod n ) x S 2 h ( x , k ) = { k + 1 ( mod n ) x S 0 2 k ( mod n ) x S 1 k x S 2 {\displaystyle {\begin{aligned}g(x,k)&={\begin{cases}k&x\in S_{0}\2円k{\pmod {n}}&x\in S_{1}\\k+1{\pmod {n}}&x\in S_{2}\end{cases}}\\h(x,k)&={\begin{cases}k+1{\pmod {n}}&x\in S_{0}\2円k{\pmod {n}}&x\in S_{1}\\k&x\in S_{2}\end{cases}}\end{aligned}}} {\displaystyle {\begin{aligned}g(x,k)&={\begin{cases}k&x\in S_{0}\2円k{\pmod {n}}&x\in S_{1}\\k+1{\pmod {n}}&x\in S_{2}\end{cases}}\\h(x,k)&={\begin{cases}k+1{\pmod {n}}&x\in S_{0}\2円k{\pmod {n}}&x\in S_{1}\\k&x\in S_{2}\end{cases}}\end{aligned}}}
input: a: a generator of G
 b: an element of G
output: An integer x such that ax = b, or failure
Initialise i ← 0, a0 ← 0, b0 ← 0, x0 ← 1 ∈ G
loop
 ii + 1
 xif(xi−1),
 aig(xi−1, ai−1),
 bih(xi−1, bi−1)
 x2i−1f(x2i−2),
 a2i−1g(x2i−2, a2i−2),
 b2i−1h(x2i−2, b2i−2)
 x2if(x2i−1),
 a2ig(x2i−1, a2i−1),
 b2ih(x2i−1, b2i−1)
while xix2i
rbib2i
if r = 0 return failure
return r−1(a2iai) mod n

Example

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Consider, for example, the group generated by 2 modulo N = 1019 {\displaystyle N=1019} {\displaystyle N=1019} (the order of the group is n = 1018 {\displaystyle n=1018} {\displaystyle n=1018}, 2 generates the group of units modulo 1019). The algorithm is implemented by the following C++ program:

#include<stdio.h>
constintn=1018,N=n+1;/* N = 1019 -- prime */
constintalpha=2;/* generator */
constintbeta=5;/* 2^{10} = 1024 = 5 (N) */
voidnew_xab(int&x,int&a,int&b){
switch(x%3){
case0:x=x*x%N;a=a*2%n;b=b*2%n;break;
case1:x=x*alpha%N;a=(a+1)%n;break;
case2:x=x*beta%N;b=(b+1)%n;break;
}
}
intmain(void){
intx=1,a=0,b=0;
intX=x,A=a,B=b;
for(inti=1;i<n;++i){
new_xab(x,a,b);
new_xab(X,A,B);
new_xab(X,A,B);
printf("%3d %4d %3d %3d %4d %3d %3d\n",i,x,a,b,X,A,B);
if(x==X)break;
}
return0;
}

The results are as follows (edited):

 i x a b X A B
------------------------------
 1 2 1 0 10 1 1
 2 10 1 1 100 2 2
 3 20 2 1 1000 3 3
 4 100 2 2 425 8 6
 5 200 3 2 436 16 14
 6 1000 3 3 284 17 15
 7 981 4 3 986 17 17
 8 425 8 6 194 17 19
..............................
48 224 680 376 86 299 412
49 101 680 377 860 300 413
50 505 680 378 101 300 415
51 1010 681 378 1010 301 416

That is 2 681 5 378 = 1010 = 2 301 5 416 ( mod 1019 ) {\displaystyle 2^{681}5^{378}=1010=2^{301}5^{416}{\pmod {1019}}} {\displaystyle 2^{681}5^{378}=1010=2^{301}5^{416}{\pmod {1019}}} and so ( 416 378 ) γ = 681 301 ( mod 1018 ) {\displaystyle (416-378)\gamma =681-301{\pmod {1018}}} {\displaystyle (416-378)\gamma =681-301{\pmod {1018}}}, for which γ 1 = 10 {\displaystyle \gamma _{1}=10} {\displaystyle \gamma _{1}=10} is a solution as expected. As n = 1018 {\displaystyle n=1018} {\displaystyle n=1018} is not prime, there is another solution γ 2 = 519 {\displaystyle \gamma _{2}=519} {\displaystyle \gamma _{2}=519}, for which 2 519 = 1014 = 5 ( mod 1019 ) {\displaystyle 2^{519}=1014=-5{\pmod {1019}}} {\displaystyle 2^{519}=1014=-5{\pmod {1019}}} holds.

Complexity

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The running time is approximately O ( n ) {\displaystyle {\mathcal {O}}({\sqrt {n}})} {\displaystyle {\mathcal {O}}({\sqrt {n}})}. If used together with the Pohlig–Hellman algorithm, the running time of the combined algorithm is O ( p ) {\displaystyle {\mathcal {O}}({\sqrt {p}})} {\displaystyle {\mathcal {O}}({\sqrt {p}})}, where p {\displaystyle p} {\displaystyle p} is the largest prime factor of n {\displaystyle n} {\displaystyle n}.

References

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Primality tests
Prime-generating
Integer factorization
Multiplication
Euclidean division
Discrete logarithm
Greatest common divisor
Modular square root
Other algorithms
  • Italics indicate that algorithm is for numbers of special forms

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