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Statistics for fixed points of x → xx
mod p
Matthew Friedrichsen and Joshua Holden
Forging a (variant) ElGamal Digital Signature
Frank the Forger wants to solve for r and s in:
(1) gH(m)
≡ ys
rr
(mod p).
He knows m, g, y, and p but not the discrete log of
y mod p base g. He could:
calculate the discrete log of y,
or he could solve rr
≡ gH(m)
y−s
(mod p) for r.
We wish to shed light on the difficulty of the second
attack by studying the self-power map,
x → xx
mod p.
Figure 1: The self-power map modulo 13
Is x → xx
mod p “random”?
Heuristic 1.For all p, if x, y are chosen uniformly at random from {1, . . . , p − 1} with
ordp x = d, then
Pr[xx
≡ y (mod p)] ≈
1
d if ordp y | d,
0 otherwise.
Counts of the fixed points are not normally distributed
This work investigates the number of fixed points of the self-power map, i.e., solutions to
(2) xx
≡ x (mod p).
Let F(p) be the number of solutions to (2) such that 1 ≤ x ≤ p − 1. How are these
counts distributed? The figures show that the distribution is not (quite) normal.
Figure 2: Histogram and Probability Plot of z-statistics for 238 six-digit primes
The counts for most orders are binomially distributed
Let Fd(p) be the number of solutions to (2) with 1 ≤ x ≤ p − 1 and ordp x = d.
Assume x values behave independently.
Prediction 2.
Pr[Fd(p) = k] =
φ(d)
k
1
d
k
d − 1
d
φ(d)−k
A chi-squared goodness-of-fit test gives
p-value ≈ 0.198
which does not refute the prediction.
We also tried a sliding window chi-squared
test on the data sorted by order. The
resulting p-values should be uniformly
distributed but are not for small and large d.
1
10
100
1000
10000
100000
0 0.2 0.4 0.6 0.8 1
Order
p-value
Figure 3: Logarithmic plot showing p-values of
the sliding window test for 238 six-digit primes
Dependencies matter for small and large orders
For small and large orders it turns out that the independence assumption is violated.
Theorem 3. (a) The x-values of order 3 cannot both be fixed points.
(b) The x-values of order 4 cannot both be fixed points.
(c) The x-values of order 6 are both fixed points or neither is.
There are similar effects for d = (p − 1)/3 and d = (p − 1)/4, and possibly a few others.
Number of primes: predicted (P), observed (O), and not possible (N).
Fd(p) = 0
Fd(p) = 1
Fd(p) = 2
0 25 50 75 100
n = 116, p = 0.79
N
O
O
P
P
order 3
0 25 50 75 100
n = 120, p = 0.36
N
O
O
P
P
order 4
0 25 50 75 100
n = 116, p = 0.8
N
O
O
P
P
order 6
Number of primes: predicted (P), observed (O), and not possible (N).
Fd(p) = 0
Fd(p) = 1
Fd(p) = 2
0 25 50 75 100
n = 116, p = 0.46
O
O
O
P
P
P
order (p − 1) 3
0 25 50 75 100
n = 54, p = 0.33
O
O
O
P
P
P
order (p − 1) 4, p ≡ 1 (mod 8)
0 25 50 75 100
n = 66, p = 0.48
N
O
O
P
P
order (p − 1) 4, p ≡ 5 (mod 8)
Figure 4: Predictions and observations for fixed points of small and large orders in 238 six-digit primes
Our predictions based on these dependencies are not refuted by chi-squared tests.

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Statistics for fixed points of x ↦ x^x mod p

  • 1. Statistics for fixed points of x → xx mod p Matthew Friedrichsen and Joshua Holden Forging a (variant) ElGamal Digital Signature Frank the Forger wants to solve for r and s in: (1) gH(m) ≡ ys rr (mod p). He knows m, g, y, and p but not the discrete log of y mod p base g. He could: calculate the discrete log of y, or he could solve rr ≡ gH(m) y−s (mod p) for r. We wish to shed light on the difficulty of the second attack by studying the self-power map, x → xx mod p. Figure 1: The self-power map modulo 13 Is x → xx mod p “random”? Heuristic 1.For all p, if x, y are chosen uniformly at random from {1, . . . , p − 1} with ordp x = d, then Pr[xx ≡ y (mod p)] ≈ 1 d if ordp y | d, 0 otherwise. Counts of the fixed points are not normally distributed This work investigates the number of fixed points of the self-power map, i.e., solutions to (2) xx ≡ x (mod p). Let F(p) be the number of solutions to (2) such that 1 ≤ x ≤ p − 1. How are these counts distributed? The figures show that the distribution is not (quite) normal. Figure 2: Histogram and Probability Plot of z-statistics for 238 six-digit primes The counts for most orders are binomially distributed Let Fd(p) be the number of solutions to (2) with 1 ≤ x ≤ p − 1 and ordp x = d. Assume x values behave independently. Prediction 2. Pr[Fd(p) = k] = φ(d) k 1 d k d − 1 d φ(d)−k A chi-squared goodness-of-fit test gives p-value ≈ 0.198 which does not refute the prediction. We also tried a sliding window chi-squared test on the data sorted by order. The resulting p-values should be uniformly distributed but are not for small and large d. 1 10 100 1000 10000 100000 0 0.2 0.4 0.6 0.8 1 Order p-value Figure 3: Logarithmic plot showing p-values of the sliding window test for 238 six-digit primes Dependencies matter for small and large orders For small and large orders it turns out that the independence assumption is violated. Theorem 3. (a) The x-values of order 3 cannot both be fixed points. (b) The x-values of order 4 cannot both be fixed points. (c) The x-values of order 6 are both fixed points or neither is. There are similar effects for d = (p − 1)/3 and d = (p − 1)/4, and possibly a few others. Number of primes: predicted (P), observed (O), and not possible (N). Fd(p) = 0 Fd(p) = 1 Fd(p) = 2 0 25 50 75 100 n = 116, p = 0.79 N O O P P order 3 0 25 50 75 100 n = 120, p = 0.36 N O O P P order 4 0 25 50 75 100 n = 116, p = 0.8 N O O P P order 6 Number of primes: predicted (P), observed (O), and not possible (N). Fd(p) = 0 Fd(p) = 1 Fd(p) = 2 0 25 50 75 100 n = 116, p = 0.46 O O O P P P order (p − 1) 3 0 25 50 75 100 n = 54, p = 0.33 O O O P P P order (p − 1) 4, p ≡ 1 (mod 8) 0 25 50 75 100 n = 66, p = 0.48 N O O P P order (p − 1) 4, p ≡ 5 (mod 8) Figure 4: Predictions and observations for fixed points of small and large orders in 238 six-digit primes Our predictions based on these dependencies are not refuted by chi-squared tests.