math/ipa.sage
ipa.sageRaw
1# This file contains two Inner Product Argument implementations:
2# - Bulletproofs version: https://eprint.iacr.org/2017/1066.pdf
3# - Halo version: https://eprint.iacr.org/2019/1021.pdf
4
5
6
7# IPA_bulletproofs implements the IPA version from the Bulletproofs paper: https://eprint.iacr.org/2017/1066.pdf
8# https://doc-internal.dalek.rs/bulletproofs/notes/inner_product_proof/index.html
9class IPA_bulletproofs(object):
10 def __init__(self, F, E, g, d):
11 self.g = g
12 self.F = F
13 self.E = E
14 self.d = d
15 # TODO:
16 # Setup:
17 self.h = E.random_element() # TMP
18 self.gs = random_values(E, d)
19 self.hs = random_values(E, d)
20
21 # a: aᵢ ∈ 𝔽 coefficients of p(X)
22 # r: blinding factor
23 def commit(self, a, b):
24 P = inner_product_point(a, self.gs) + inner_product_point(b, self.hs)
25 return P
26
27 def evaluate(self, a, x_powers):
28 return inner_product_field(a, x_powers)
29
30 def ipa(self, a_, b_, u, U):
31 G = self.gs
32 H = self.hs
33 a = a_
34 b = b_
35
36 k = int(math.log(self.d, 2))
37 L = [None] * k
38 R = [None] * k
39
40 for j in reversed(range(0, k)):
41 m = len(a)/2
42 a_lo = a[:m]
43 a_hi = a[m:]
44 b_lo = b[:m]
45 b_hi = b[m:]
46 H_lo = H[:m]
47 H_hi = H[m:]
48 G_lo = G[:m]
49 G_hi = G[m:]
50
51 # Lⱼ = <a'ₗₒ, G'ₕᵢ> + [lⱼ] H + [<a'ₗₒ, b'ₕᵢ>] U
52 L[j] = inner_product_point(a_lo, G_hi) + inner_product_point(b_hi, H_lo) + int(inner_product_field(a_lo, b_hi)) * U
53 # Rⱼ = <a'ₕᵢ, G'ₗₒ> + [rⱼ] H + [<a'ₕᵢ, b'ₗₒ>] U
54 R[j] = inner_product_point(a_hi, G_lo) + inner_product_point(b_lo, H_hi) + int(inner_product_field(a_hi, b_lo)) * U
55
56 # use the random challenge uⱼ ∈ 𝕀 generated by the verifier
57 u_ = u[j] # uⱼ
58 u_inv = u[j]^(-1) # uⱼ⁻¹
59
60 a = vec_add(vec_scalar_mul_field(a_lo, u_), vec_scalar_mul_field(a_hi, u_inv))
61 b = vec_add(vec_scalar_mul_field(b_lo, u_inv), vec_scalar_mul_field(b_hi, u_))
62 G = vec_add(vec_scalar_mul_point(G_lo, u_inv), vec_scalar_mul_point(G_hi, u_))
63 H = vec_add(vec_scalar_mul_point(H_lo, u_), vec_scalar_mul_point(H_hi, u_inv))
64
65 assert len(a)==1
66 assert len(b)==1
67 assert len(G)==1
68 assert len(H)==1
69 # a, b, G have length=1
70 # L, R are the "cross-terms" of the inner product
71 return a[0], b[0], G[0], H[0], L, R
72
73 def verify(self, P, a, v, x_powers, u, U, L, R, b_ipa, G_ipa, H_ipa):
74 b = b_ipa
75 G = G_ipa
76 H = H_ipa
77
78 # Q_0 = P' ⋅ ∑ ( [uⱼ²] Lⱼ + [uⱼ⁻²] Rⱼ)
79 C = P
80 for j in range(len(L)):
81 u_ = u[j] # uⱼ
82 u_inv = u[j]^(-1) # uⱼ⁻²
83
84 # ∑ ( [uⱼ²] Lⱼ + [uⱼ⁻²] Rⱼ)
85 C = C + int(u_^2) * L[j] + int(u_inv^2) * R[j]
86
87 D = int(a) * G + int(b) * H + int(a * b)*U
88
89 return C == D
90
91# IPA_halo implements the modified IPA from the Halo paper: https://eprint.iacr.org/2019/1021.pdf
92class IPA_halo(object):
93 def __init__(self, F, E, g, d):
94 self.g = g
95 self.F = F
96 self.E = E
97 self.d = d
98
99 self.h = E.random_element() # TMP
100 self.gs = random_values(E, d)
101 self.hs = random_values(E, d)
102 print(" h=", self.h)
103 print(" G=", self.gs)
104 print(" H=", self.hs)
105
106 def commit(self, a, r):
107 P = inner_product_point(a, self.gs) + r * self.h
108 return P
109
110 def evaluate(self, a, x_powers):
111 return inner_product_field(a, x_powers)
112
113 def ipa(self, a_, x_powers, u, U): # prove
114 print(" method ipa():")
115 G = self.gs
116 a = a_
117 b = x_powers
118
119 k = int(math.log(self.d, 2))
120 l = [None] * k
121 r = [None] * k
122 L = [None] * k
123 R = [None] * k
124
125 for j in reversed(range(0, k)):
126 print(" j =", j)
127 print(" len(a) = n =", len(a))
128 print(" m = n/2 =", len(a)/2)
129 m = len(a)/2
130 a_lo = a[:m]
131 a_hi = a[m:]
132 b_lo = b[:m]
133 b_hi = b[m:]
134 G_lo = G[:m]
135 G_hi = G[m:]
136
137 print(" Split into a_lo,hi b_lo,hi, G_lo,hi:")
138 print(" a", a)
139 print(" a_lo", a_lo)
140 print(" a_hi", a_hi)
141 print(" b", b)
142 print(" b_lo", b_lo)
143 print(" b_hi", b_hi)
144 print(" G", G)
145 print(" G_lo", G_lo)
146 print(" G_hi", G_hi)
147
148 l[j] = self.F.random_element() # random blinding factor
149 r[j] = self.F.random_element() # random blinding factor
150 print(" random blinding factors:")
151 print(" l[j]", l[j])
152 print(" r[j]", r[j])
153
154 # Lⱼ = <a'ₗₒ, G'ₕᵢ> + [lⱼ] H + [<a'ₗₒ, b'ₕᵢ>] U
155 L[j] = inner_product_point(a_lo, G_hi) + int(l[j]) * self.h + int(inner_product_field(a_lo, b_hi)) * U
156 # Rⱼ = <a'ₕᵢ, G'ₗₒ> + [rⱼ] H + [<a'ₕᵢ, b'ₗₒ>] U
157 R[j] = inner_product_point(a_hi, G_lo) + int(r[j]) * self.h + int(inner_product_field(a_hi, b_lo)) * U
158
159 print(" Compute Lⱼ = <a'ₗₒ, G'ₕᵢ> + [lⱼ] H + [<a'ₗₒ, b'ₕᵢ>] U")
160 print(" L[j]", L[j])
161 print(" Compute Rⱼ = <a'ₕᵢ, G'ₗₒ> + [rⱼ] H + [<a'ₕᵢ, b'ₗₒ>] U")
162 print(" R[j]", R[j])
163
164 # use the random challenge uⱼ ∈ 𝕀 generated by the verifier
165 u_ = u[j] # uⱼ
166 u_inv = self.F(u[j])^(-1) # uⱼ⁻¹
167 print(" u_j", u_)
168 print(" u_j^-1", u_inv)
169
170 a = vec_add(vec_scalar_mul_field(a_lo, u_), vec_scalar_mul_field(a_hi, u_inv))
171 b = vec_add(vec_scalar_mul_field(b_lo, u_inv), vec_scalar_mul_field(b_hi, u_))
172 G = vec_add(vec_scalar_mul_point(G_lo, u_inv), vec_scalar_mul_point(G_hi, u_))
173 print(" new a, b, G")
174 print(" a =", a)
175 print(" b =", b)
176 print(" G =", G)
177
178 assert len(a)==1
179 assert len(b)==1
180 assert len(G)==1
181 # a, b, G have length=1
182 # l, r are random blinding factors
183 # L, R are the "cross-terms" of the inner product
184 return a[0], b[0], G[0], l, r, L, R
185
186 def verify(self, P, a, v, x_powers, r, u, U, lj, rj, L, R, b_ipa, G_ipa):
187 print("methid verify()")
188 # b = x_powers
189 # G = self.gs
190 b = b_ipa # TODO b_0 & G_0 will be computed by the client
191 G = G_ipa
192
193 # k = int(math.log(self.d, 2))
194 # s = build_s_from_us(u, k)
195
196 # synthetic blinding factor
197 # r' = r + ∑ ( lⱼ uⱼ² + rⱼ uⱼ⁻²)
198 print(" synthetic blinding factor r' = r + ∑ ( lⱼ uⱼ² + rⱼ uⱼ⁻²)")
199 r_ = r
200 print(" r_ =", r_)
201 # Q_0 = P' ⋅ ∑ ( [uⱼ²] Lⱼ + [uⱼ⁻²] Rⱼ)
202 print(" Q_0 = P' ⋅ ∑ ( [uⱼ²] Lⱼ + [uⱼ⁻²] Rⱼ)")
203 Q_0 = P
204 print(" Q_0 =", Q_0)
205 for j in range(len(u)):
206 print(" j =", j)
207 u_ = u[j] # uⱼ
208 u_inv = u[j]^(-1) # uⱼ⁻²
209
210 # ∑ ( [uⱼ²] Lⱼ + [uⱼ⁻²] Rⱼ)
211 Q_0 = Q_0 + int(u[j]^2) * L[j] + int(u_inv^2) * R[j]
212 print(" Q_0 =", Q_0)
213
214 r_ = r_ + lj[j] * (u_^2) + rj[j] * (u_inv^2)
215 print(" r_ =", r_)
216
217 Q_1 = int(a) * G + int(r_) * self.h + int(a * b)*U
218 print(" Q_1", Q_1)
219 # Q_1_ = int(a) * (G + int(b)*U) + int(r_) * self.h
220
221 return Q_0 == Q_1
222
223
224# def build_s_from_us(u, k):
225# s = None*k
226# for i in range(k):
227# e = 1
228# for j in range(k):
229# e = e*u[j]
230# # s[i] =
231# return s
232
233
234
235
236def powers_of(g, d):
237 r = [None] * d
238 for i in range(d):
239 r[i] = g^i
240 return r
241
242
243def multiples_of(g, d):
244 r = [None] * d
245 for i in range(d):
246 r[i] = g*i
247 return r
248
249def random_values(G, d):
250 r = [None] * d
251 for i in range(d):
252 r[i] = G.random_element()
253 return r
254
255def inner_product_field(a, b):
256 assert len(a) == len(b)
257 c = 0
258 for i in range(len(a)):
259 c = c + a[i] * b[i]
260
261 return c
262
263def inner_product_point(a, b):
264 assert len(a) == len(b)
265 c = 0
266 for i in range(len(a)):
267 c = c + int(a[i]) * b[i]
268
269 return c
270
271def vec_add(a, b):
272 assert len(a) == len(b)
273 return [x + y for x, y in zip(a, b)]
274
275def vec_mul(a, b):
276 assert len(a) == len(b)
277 return [x * y for x, y in zip(a, b)]
278
279def vec_scalar_mul_field(a, n):
280 r = [None]*len(a)
281 for i in range(len(a)):
282 r[i] = a[i]*n
283 return r
284
285def vec_scalar_mul_point(a, n):
286 r = [None]*len(a)
287 for i in range(len(a)):
288 r[i] = a[i]*int(n)
289 return r
290
291