def from_source(cls, tensor_name, source, **kwargs):
spdz = cls.get_spdz()
q_field = kwargs['q_field'] if 'q_field' in kwargs else spdz.q_field
if 'encoder' in kwargs:
encoder = kwargs['encoder']
else:
base = kwargs['base'] if 'base' in kwargs else 10
frac = kwargs['frac'] if 'frac' in kwargs else 4
encoder = FixedPointEndec(q_field, base, frac)
if isinstance(source, np.ndarray):
source = encoder.encode(source)
_pre = urand_tensor(q_field, source)
spdz.communicator.remote_share(share=_pre,
tensor_name=tensor_name,
party=spdz.other_parties[0])
for _party in spdz.other_parties[1:]:
r = urand_tensor(q_field, source)
spdz.communicator.remote_share(share=r - _pre,
tensor_name=tensor_name,
party=_party)
_pre = r
share = source - _pre
elif isinstance(source, Party):
share = spdz.communicator.get_share(tensor_name=tensor_name,
party=source)[0]
else:
raise ValueError(f"type={type(source)}")
return FixedPointTensor(share, spdz.q_field, encoder, tensor_name)
def from_source(cls, tensor_name, source, **kwargs):
spdz = cls.get_spdz()
if 'encoder' in kwargs:
encoder = kwargs['encoder']
else:
base = kwargs['base'] if 'base' in kwargs else 10
frac = kwargs['frac'] if 'frac' in kwargs else 4
q_field = kwargs['q_field'] if 'q_field' in kwargs else spdz.q_field
encoder = fixedpoint_numpy.FixedPointEndec(q_field, base, frac)
if isinstance(source, Table):
source = encoder.encode(source)
_pre = urand_tensor(spdz.q_field, source)
spdz.communicator.remote_share(share=_pre,
tensor_name=tensor_name,
party=spdz.other_parties[0])
for _party in spdz.other_parties[1:]:
r = urand_tensor(spdz.q_field, source)
spdz.communicator.remote_share(share=_table_binary_op(
r, _pre, spdz.q_field, operator.sub),
tensor_name=tensor_name,
party=_party)
_pre = r
share = _table_binary_op(source, _pre, spdz.q_field, operator.sub)
elif isinstance(source, Party):
share = spdz.communicator.get_share(tensor_name=tensor_name,
party=source)[0]
else:
raise ValueError(f"type={type(source)}")
return FixedPointTensor(share, spdz.q_field, encoder, tensor_name)
def _cross(self_index, other_index):
_c = dot(a, b)
encrypted_a = encrypt_tensor(a, public_key)
communicator.remote_encrypted_tensor(encrypted=encrypted_a, tag=f"{name}_a_{self_index}")
r = urand_tensor(q_field, _c)
_p, (ea,) = communicator.get_encrypted_tensors(tag=f"{name}_a_{other_index}")
eab = dot(ea, b)
eab += r
_c -= r
communicator.remote_encrypted_cross_tensor(encrypted=eab,
parties=_p,
tag=f"{name}_cross_a_{other_index}_b_{self_index}")
crosses = communicator.get_encrypted_cross_tensors(tag=f"{name}_cross_a_{self_index}_b_{other_index}")
for eab in crosses:
_c += decrypt_tensor(eab, private_key, [object])
return _c
def beaver_triplets(a_tensor, b_tensor, dot, q_field, he_key_pair,
communicator: Communicator, name):
public_key, private_key = he_key_pair
a = rand_tensor(q_field, a_tensor)
b = rand_tensor(q_field, b_tensor)
c = dot(a, b)
# broadcast encrypted a and encrypted b
if communicator.party_idx == 0:
encrypted_a = encrypt_tensor(a, public_key)
encrypted_b = encrypt_tensor(b, public_key)
communicator.remote_encrypted_tensor(encrypted=encrypted_a,
tag=f"{name}_a")
communicator.remote_encrypted_tensor(encrypted=encrypted_b,
tag=f"{name}_b")
# get encrypted a and b
if communicator.party_idx == 1:
r = urand_tensor(q_field, c)
_p, encrypted_a_list = communicator.get_encrypted_tensors(
tag=f"{name}_a")
_, encrypted_b_list = communicator.get_encrypted_tensors(
tag=f"{name}_b")
cross = dot(encrypted_a_list[0], b) + dot(a, encrypted_b_list[0])
cross += r
c -= r
communicator.remote_encrypted_cross_tensor(encrypted=cross,
parties=_p,
tag=name)
if communicator.party_idx == 0:
# get cross terms
crosses = communicator.get_encrypted_cross_tensors(tag=name)
for cross in crosses:
c += decrypt_tensor(cross, private_key, [object])
return a, b, c % q_field
