def gen_threshold_sign(self, h, m, s, shares):
shaTSS = Shamir(self.t, self.n)
k = shaTSS.SC(self.p, shares).list()[_sage_const_0]
kk = bin(int(str(k)))[_sage_const_2:]
R = m.parent()
f_len = int(kk[:_sage_const_8], _sage_const_2)
fs_len = int(kk[_sage_const_8:_sage_const_16], _sage_const_2)
R = m.parent()
f = R([
-_sage_const_1 * int(x)
for x in kk[_sage_const_16:_sage_const_16 + f_len]
])
fs = R([
-_sage_const_1 * int(x)
for x in kk[_sage_const_16 + f_len:_sage_const_16 + f_len + fs_len]
])
x = auxmath.normilize_coeffs(-(_sage_const_1 / self.q) * m * fs)
y = auxmath.normilize_coeffs(-(_sage_const_1 / self.q) * m * f)
s0 = x * f + y * fs
s_res = R(s + s0)
b = s_res * auxmath.normilize_coeffs2(s_res * self.h0 - m, self.q)
print(b)
print(b.norm(_sage_const_2))
def gen_threshold_sign(self, h, m, s, i, shares):
self.get_info()
shaTSS = Shamir(self.t, self.n)
if i == _sage_const_0:
print('UPDATE')
print('UPDATE')
print('UPDATE')
print('UPDATE')
self.fs = None
self.f = None
print(shares)
# if self.t_new == None:
# k = shaTSS.SC(self.p, shares).list()[0]
# else:
# M = []
# for i in range(self.t+self.t_new):
# row = [0] * (self.t+self.t_new)
# if i < self.t_new:
# row[i] = self.p
# else:
# row[i] = self.H / self.p
# for j in range(self.t_new):
# row[j] = shares[j][0] ** (i-self.t_new+1)
# M.append(row)
# M = matrix(QQ, M)
# target = [x[1] for x in shares[:self.t_new]] + [0]*self.t
# c = Babai_CVP(M, target)
# R = Integers(self.p)
# k = R((self.p/self.H)*c[self.t_new])
R1 = PolynomialRing(ZZ, names=('x', ))
(x, ) = R1._first_ngens(1)
phi = x**self.N - _sage_const_1
Rx = R1.quotient_by_principal_ideal(phi)
if self.f == None or self.fs == None:
k = shaTSS.SC(self.p, shares).list()[_sage_const_0]
kk = bin(int(str(k)))[_sage_const_2:]
f_len = int(kk[:_sage_const_8], _sage_const_2)
fs_len = int(kk[_sage_const_8:_sage_const_16], _sage_const_2)
print(k)
self.f = Rx([
-_sage_const_1 * int(x)
for x in kk[_sage_const_16:_sage_const_16 + f_len]
])._polynomial
self.fs = Rx([
-_sage_const_1 * int(x)
for x in kk[_sage_const_16 + f_len:_sage_const_16 + f_len +
fs_len]
])._polynomial
T = int(kk[_sage_const_16 + f_len + fs_len:], _sage_const_2)
print(T)
if T != self.T:
return -_sage_const_1
x = Rx(normilize_coeffs(
-_sage_const_1 / self.q * m * self.fs))._polynomial % self.q
y = Rx(normilize_coeffs(
_sage_const_1 / self.q * m * self.f))._polynomial % self.q
s0 = (Rx(x * self.f)._polynomial % self.q +
Rx(y * self.fs)._polynomial % self.q) % self.q
s = s + s0
return s