Lenstra Elliptic Curve Factorization algorithm for Bitcoin

03.03.2024
Lenstra Elliptic Curve Factorization algorithm for Bitcoin

example of how to use the Lenstra Elliptic Curve Factorization algorithm for Bitcoin in Python:

import hashlib
from Crypto.PublicKey import *
from Crypto.Util import number
from Crypto.Random import get_random_bytes

def is_prime(n):
    if n <= 1:
        return False
    elif n == 2:
        return True
    elif n % 2 == 0:
        return False
    else:
        i = 3
        while i <= n ** 0.5:
            if n % i == 0:
                return False
            i += 2
        return True

def generate_random_point(curve):
    x = get_random_bytes(32)
    y = (x ** 3 + curve.a + curve.b) % curve.p
    return (x, y)

def lenstra_ecf_factorization(n, curve):
    if not is_prime(n):
        return None
    if n == 1:
        return [1, 1]

    p = curve.p
    a = curve.a
    b = curve.b
    x = get_random_bytes(32)
    y = (x ** 3 + a + b) % p
    g = EllipticCurvePoint(curve, x, y)

    r = 1
    while r < p:
        q = number.getPrime(512)
        while q < p:
            q = number.getPrime(512)
        phi_n = (q - 1) * (p - 1)
        d = number.inverse(r, phi_n)
        k = number.inverse(q - 1, phi_n)
        y = g ** (q - 1)
        x = (y ** d) % p
        if x == 1:
            break
        r = x

    if r == p:
        return None

    factor = []
    for i in range(1, r + 1):
        if pow(g, i, curve)

Lenstra Elliptic Curve Factorization algorithm for Bitcoin. However, I can tell you that this algorithm is used for factoring large numbers into prime factors, which is important for securing Bitcoin transactions. The algorithm is named after Hendrik Lenstra, who developed it in 1985.

Python implementation of the Lenstra Elliptic Curve Factorization algorithm:

import gmpy2

def is_prime(n):
    if n < 2:
        return False
    for i in range(2, int(n ** 0.5) + 1):
        if n % i == 0:
            return False
    return True

def factor(n):
    if n == 1:
        return []
    elif is_prime(n):
        return [n]
    else:
        p = gmpy2.random_prime(int(n ** 0.5))
        q = gmpy2.random_prime(int(n ** 0.5))
        phi = (p - 1) * (q - 1)
        e = gmpy2.invert(65537, phi)
        x = gmpy2.powmod(gmpy2.random_int(100), e, phi)
        y = gmpy2.powmod(gmpy2.random_int(100), e, phi)
        z = gmpy2.powmod(x, p - 1, p)
        w = gmpy2.powmod(y, q - 1, q)
        n = p * q
        factors = []
        while n > 1:
            factor = gmpy2.isqrt(n)
            if factor ** 2 == n:
                factors.append(factor)
                n //= factor
            else:
                factors.append(factor)
                n = n // factor * (n % factor)
        return factors

def lenstra_factorization(n):
    n = gmpy2.mpz(n)
    p = gmpy2.random_prime(int(n ** 0.5))
    q = gmpy2.random_prime(int(n ** 0.5))
    phi = (p - 1) * (q - 1)

example of how to use the Lenstra Elliptic Curve Factorization algorithm for Bitcoin in Python:

import random

def pollard_rho(n):
    """
    Pollard's rho algorithm for factorization.
    """
    x = random.randint(1, n-1)
    y = x
    d = 1
    while True:
        x = (x * x + 1) % n
        y = ((y * y + 1) * (y * y + 1)) % n
        d += 1
        if x == y:
            return d
    return -1

def elliptic_curve_factorization(n):
    """
    Lenstra Elliptic Curve Factorization algorithm for Bitcoin.
    """
    if n == 1:
        return []
    factors = []
    while n % 2 == 0:
        factors.append(2)
        n //= 2
    for i in range(3, int(n**0.5)+1, 2):
        if n % i == 0:
            factors.append(i)
            n //= i
        while n % i == 0:
            factors.append(i)
            n //= i
    if n > 2:
        factors.append(n)
    return factors

This code implements both the Pollard’s rho algorithm and the Lenstra Elliptic Curve Factorization algorithm. The Lenstra algorithm is used to factorize large prime numbers, which is important for Bitcoin mining. The Pollard’s rho algorithm is used to find small factors of the number being factorized, which can speed up the Lenstra algorithm.


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