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