Add ring signatures sage implementation (bLSAG)

sigma.sage

@@ -0,0 +1,213 @@
+from hashlib import sha256
+
+# Implementation of Sigma protocol & OR proofs
+
+
+def hash_two_points(a, b):
+    h = sha256((str(a)+str(b)).encode('utf-8'))
+    return int(h.hexdigest(), 16)
+
+def generic_verify(g, X, A, c, z):
+    return g * int(z) == X * int(c) + A
+
+###
+# Sigma protocol interactive
+###
+
+class Prover_interactive(object):
+    def __init__(self, F, g):
+        self.F = F # Z_p
+        self.g = g # elliptic curve generator
+
+    def new_key(self):
+        self.w = self.F.random_element()
+        X = self.g * int(self.w)
+        return X
+
+    def new_commitment(self):
+        self.a = self.F.random_element()
+        A = self.g * int(self.a)
+        return A
+
+    def gen_proof(self, c):
+        return int(self.a) + int(c) * int(self.w)
+
+class Verifier_interactive(object):
+    def __init__(self, F, g):
+        self.F = F
+        self.g = g
+
+    def new_challenge(self, A):
+        self.A = A
+        self.c = self.F.random_element()
+        return self.c
+    
+    def verify(self, X, z):
+        return self.g * int(z) == X * int(self.c) + self.A
+
+
+###
+# Sigma protocol non-interactive
+###
+class Prover(object):
+    def __init__(self, F, g):
+        self.F = F # Z_p
+        self.g = g # elliptic curve generator
+
+    def new_key(self):
+        self.w = self.F.random_element()
+        X = self.g * int(self.w)
+        return X
+
+    def gen_proof(self, X):
+        a = self.F.random_element()
+        A = self.g * int(a)
+        c = hash_two_points(A, X)
+        z = int(a) + c * int(self.w)
+        return A, z
+
+
+class Verifier(object):
+    def __init__(self, F, g):
+        self.F = F
+        self.g = g
+
+    def verify(self, X, A, z):
+        c = hash_two_points(A, X)
+        return self.g * int(z) == X * c + A
+
+class Simulator(object):
+    def __init__(self, F, g):
+        self.F = F
+        self.g = g
+
+    def simulate(self, X):
+        c = self.F.random_element()
+        z = self.F.random_element()
+        #  A = g * int(z) + X*(-int(c))
+        A = g * int(z) - X * int(c)
+        return A, c, z
+
+###
+# OR proof (with 2 parties)
+###
+
+class ORProver_2parties(object):
+    def __init__(self, F, g):
+        self.F = F # Z_p
+        self.g = g # elliptic curve generator
+
+    def new_key(self):
+        self.w = self.F.random_element()
+        X = self.g * int(self.w)
+        return X
+
+    def gen_commitments(self, xs):
+        # gen commitment A
+        self.a = self.F.random_element()
+        A = self.g * int(self.a)
+
+        # run the simulator for 1-b
+        sim = Simulator(self.F, self.g)
+        A_1, c_1, z_1 = sim.simulate(xs[1])
+
+        self.A_1 = A_1
+        self.c_1 = c_1
+        self.z_1 = z_1
+
+        return [A, A_1]
+
+    def gen_proof(self, s):
+        # split the challenge s = c xor c_1
+        c = int(s) ^^ int(self.c_1)
+        # compute z
+        z = int(self.a) + int(c) * int(self.w)
+        # note, here the order of the returned elements is always the same, in
+        # a real-world implementation would be shuffled
+        return [c, self.c_1], [z, self.z_1]
+
+class ORVerifier_2parties(object):
+    def __init__(self, F, g):
+        self.F = F
+        self.g = g
+
+    def new_challenge(self, As):
+        self.As = As
+        self.s = self.F.random_element()
+        return self.s
+
+    def verify(self, Xs, cs, zs):
+        assert self.s == int(cs[0]) ^^ int(cs[1])
+        assert self.g * int(zs[0]) == Xs[0] * int(cs[0]) + self.As[0]
+        assert self.g * int(zs[1]) == Xs[1] * int(cs[1]) + self.As[1]
+
+###
+# OR proof (with n parties)
+###
+
+class ORProver(object):
+    def __init__(self, F, g):
+        self.F = F # Z_p
+        self.g = g # elliptic curve generator
+
+    def new_key(self):
+        self.w = self.F.random_element()
+        X = self.g * int(self.w)
+        return X
+
+    def gen_commitments(self, xs):
+        # gen commitment A
+        self.a = self.F.random_element()
+        A = self.g * int(self.a)
+        self.As = [A]
+
+
+        # run the simulator for the rest of Xs
+        sim = Simulator(self.F, self.g)
+        self.cs = []
+        self.zs = []
+        for i in range(1, len(xs)):
+            A_1, c_1, z_1 = sim.simulate(xs[i])
+            self.As.append(A_1)
+            self.cs.append(c_1)
+            self.zs.append(z_1)
+
+        return self.As
+
+    def gen_proof(self, s):
+        # split the challenge s = c xor c_1 xor c_2 xor ... xor c_n
+        c = int(s)
+        for i in range(len(self.cs)):
+            c = c ^^ int(self.cs[i])
+
+        self.cs.insert(0, c) # add c at the beginning of cs array
+
+        # compute z
+        z = int(self.a) + int(c) * int(self.w)
+        self.zs.insert(0, z) # add z at the beginning of zs array
+
+        # note, here the order of the returned elements is always the same, in
+        # a real-world implementation would be shuffled
+        return self.cs, self.zs
+
+class ORVerifier(object):
+    def __init__(self, F, g):
+        self.F = F
+        self.g = g
+
+    def new_challenge(self, As):
+        self.As = As
+        self.s = self.F.random_element()
+        return self.s
+
+    def verify(self, Xs, cs, zs):
+        # check s == c_0 xor c_1 xor c_2 xor ... xor c_n
+        computed_s = int(cs[0])
+        for i in range(1, len(cs)):
+            computed_s = computed_s ^^ int(cs[i])
+
+        assert self.s == computed_s
+
+        # check g*z == X*c + A (in multiplicative notation would g^z ==X^c * A)
+        for i in range(len(Xs)):
+            assert self.g * int(zs[i]) == Xs[i] * int(cs[i]) + self.As[i]