mirror of
https://github.com/jb55/nostril.git
synced 2024-05-19 11:12:31 -04:00
115 lines
3.5 KiB
Python
115 lines
3.5 KiB
Python
""" Generates the constants used in secp256k1_scalar_split_lambda.
|
|
|
|
See the comments for secp256k1_scalar_split_lambda in src/scalar_impl.h for detailed explanations.
|
|
"""
|
|
|
|
load("secp256k1_params.sage")
|
|
|
|
def inf_norm(v):
|
|
"""Returns the infinity norm of a vector."""
|
|
return max(map(abs, v))
|
|
|
|
def gauss_reduction(i1, i2):
|
|
v1, v2 = i1.copy(), i2.copy()
|
|
while True:
|
|
if inf_norm(v2) < inf_norm(v1):
|
|
v1, v2 = v2, v1
|
|
# This is essentially
|
|
# m = round((v1[0]*v2[0] + v1[1]*v2[1]) / (inf_norm(v1)**2))
|
|
# (rounding to the nearest integer) without relying on floating point arithmetic.
|
|
m = ((v1[0]*v2[0] + v1[1]*v2[1]) + (inf_norm(v1)**2) // 2) // (inf_norm(v1)**2)
|
|
if m == 0:
|
|
return v1, v2
|
|
v2[0] -= m*v1[0]
|
|
v2[1] -= m*v1[1]
|
|
|
|
def find_split_constants_gauss():
|
|
"""Find constants for secp256k1_scalar_split_lamdba using gauss reduction."""
|
|
(v11, v12), (v21, v22) = gauss_reduction([0, N], [1, int(LAMBDA)])
|
|
|
|
# We use related vectors in secp256k1_scalar_split_lambda.
|
|
A1, B1 = -v21, -v11
|
|
A2, B2 = v22, -v21
|
|
|
|
return A1, B1, A2, B2
|
|
|
|
def find_split_constants_explicit_tof():
|
|
"""Find constants for secp256k1_scalar_split_lamdba using the trace of Frobenius.
|
|
|
|
See Benjamin Smith: "Easy scalar decompositions for efficient scalar multiplication on
|
|
elliptic curves and genus 2 Jacobians" (https://eprint.iacr.org/2013/672), Example 2
|
|
"""
|
|
assert P % 3 == 1 # The paper says P % 3 == 2 but that appears to be a mistake, see [10].
|
|
assert C.j_invariant() == 0
|
|
|
|
t = C.trace_of_frobenius()
|
|
|
|
c = Integer(sqrt((4*P - t**2)/3))
|
|
A1 = Integer((t - c)/2 - 1)
|
|
B1 = c
|
|
|
|
A2 = Integer((t + c)/2 - 1)
|
|
B2 = Integer(1 - (t - c)/2)
|
|
|
|
# We use a negated b values in secp256k1_scalar_split_lambda.
|
|
B1, B2 = -B1, -B2
|
|
|
|
return A1, B1, A2, B2
|
|
|
|
A1, B1, A2, B2 = find_split_constants_explicit_tof()
|
|
|
|
# For extra fun, use an independent method to recompute the constants.
|
|
assert (A1, B1, A2, B2) == find_split_constants_gauss()
|
|
|
|
# PHI : Z[l] -> Z_n where phi(a + b*l) == a + b*lambda mod n.
|
|
def PHI(a,b):
|
|
return Z(a + LAMBDA*b)
|
|
|
|
# Check that (A1, B1) and (A2, B2) are in the kernel of PHI.
|
|
assert PHI(A1, B1) == Z(0)
|
|
assert PHI(A2, B2) == Z(0)
|
|
|
|
# Check that the parallelogram generated by (A1, A2) and (B1, B2)
|
|
# is a fundamental domain by containing exactly N points.
|
|
# Since the LHS is the determinant and N != 0, this also checks that
|
|
# (A1, A2) and (B1, B2) are linearly independent. By the previous
|
|
# assertions, (A1, A2) and (B1, B2) are a basis of the kernel.
|
|
assert A1*B2 - B1*A2 == N
|
|
|
|
# Check that their components are short enough.
|
|
assert (A1 + A2)/2 < sqrt(N)
|
|
assert B1 < sqrt(N)
|
|
assert B2 < sqrt(N)
|
|
|
|
G1 = round((2**384)*B2/N)
|
|
G2 = round((2**384)*(-B1)/N)
|
|
|
|
def rnddiv2(v):
|
|
if v & 1:
|
|
v += 1
|
|
return v >> 1
|
|
|
|
def scalar_lambda_split(k):
|
|
"""Equivalent to secp256k1_scalar_lambda_split()."""
|
|
c1 = rnddiv2((k * G1) >> 383)
|
|
c2 = rnddiv2((k * G2) >> 383)
|
|
c1 = (c1 * -B1) % N
|
|
c2 = (c2 * -B2) % N
|
|
r2 = (c1 + c2) % N
|
|
r1 = (k + r2 * -LAMBDA) % N
|
|
return (r1, r2)
|
|
|
|
# The result of scalar_lambda_split can depend on the representation of k (mod n).
|
|
SPECIAL = (2**383) // G2 + 1
|
|
assert scalar_lambda_split(SPECIAL) != scalar_lambda_split(SPECIAL + N)
|
|
|
|
print(' A1 =', hex(A1))
|
|
print(' -B1 =', hex(-B1))
|
|
print(' A2 =', hex(A2))
|
|
print(' -B2 =', hex(-B2))
|
|
print(' =', hex(Z(-B2)))
|
|
print(' -LAMBDA =', hex(-LAMBDA))
|
|
|
|
print(' G1 =', hex(G1))
|
|
print(' G2 =', hex(G2))
|