async def test_cant_multiply_shares_from_different_contexts():
from honeybadgermpc.mpc import TaskProgramRunner
import asyncio
n, t, k = 9, 2, 2000
pp_elements = PreProcessedElements()
pp_elements.generate_double_shares(k, n, t)
pp_elements.generate_rands(k, n, t)
async def _prog(context):
share = context.Share(1)
return share
test_runner_1 = TaskProgramRunner(n, t)
test_runner_2 = TaskProgramRunner(n, t)
test_runner_1.add(_prog)
test_runner_2.add(_prog)
s1, s2 = await asyncio.gather(test_runner_1.join(), test_runner_2.join())
async def _prog2(context):
with raises(TypeError):
await s1[0] * s2[0]
test_runner_3 = TaskProgramRunner(
n, t, {DoubleSharingMultiply.name,
DoubleSharingMultiply()})
test_runner_3.add(_prog2)
await test_runner_3.join()
async def test_phase1(galois_field):
field = galois_field
n, t, k = 5, 2, 1
pp_elements = PreProcessedElements()
pp_elements.generate_powers(k, n, t, 1)
pp_elements.generate_rands(k, n, t)
async def verify_phase1(ctx, **kwargs):
k_ = kwargs["k"]
b_ = await ctx.preproc.get_powers(ctx, 0)[0].open()
file_prefixes = [uuid4().hex]
await pm.all_secrets_phase1(ctx, k=k, file_prefixes=file_prefixes)
file_name = f"{file_prefixes[0]}-{ctx.myid}.input"
file_path = f"{pp_elements.data_directory}{file_name}"
with open(file_path, "r") as f:
assert int(f.readline()) == field.modulus
# next line is a random share, which should open successfully
a_ = await ctx.Share(int(f.readline())).open()
assert int(f.readline()) == (a_ - b_).value
assert int(f.readline()) == k_
for i in range(1, k_ + 1):
assert (await
ctx.Share(int(f.readline())).open()).value == b_**(i)
program_runner = TaskProgramRunner(n, t)
program_runner.add(verify_phase1, k=k)
await program_runner.join()
async def test_open_future_shares():
n, t = 4, 1
pp_elements = PreProcessedElements()
pp_elements.generate_rands(1000, n, t)
pp_elements.generate_triples(1000, n, t)
async def _prog(context):
e1_, e2_ = [context.preproc.get_rand(context) for _ in range(2)]
e1, e2 = await asyncio.gather(*[e1_.open(), e2_.open()],
return_exceptions=True)
s_prod_f = e1_ * e2_
s_prod_f2 = s_prod_f * e1_
final_prod = s_prod_f2 + e1_ + e2_
final_prod_2 = final_prod * e1_
wrapped_final_prod_2 = context.Share(final_prod_2.open())
assert await s_prod_f2.open() == e1 * e1 * e2
assert await final_prod.open() == e1 * e1 * e2 + e1 + e2
assert await final_prod_2.open() == (e1 * e1 * e2 + e1 + e2) * e1
assert await wrapped_final_prod_2.open() == await final_prod_2.open()
program_runner = TaskProgramRunner(
n, t, {MixinConstants.MultiplyShare: BeaverMultiply()})
program_runner.add(_prog)
await program_runner.join()
async def test_butterfly_network():
n, t, k, delta = 3, 1, 32, -9999
pp_elements = PreProcessedElements()
pp_elements.generate_rands(1000, n, t)
pp_elements.generate_one_minus_ones(1000, n, t)
pp_elements.generate_triples(1500, n, t)
async def verify_output(ctx, **kwargs):
k, delta = kwargs["k"], kwargs["delta"]
inputs = [ctx.preproc.get_rand(ctx) for _ in range(k)]
sorted_input = sorted(await ctx.ShareArray(inputs).open(),
key=lambda x: x.value)
share_arr = await butterfly.butterfly_network_helper(ctx,
k=k,
delta=delta,
inputs=inputs)
outputs = await share_arr.open()
assert len(sorted_input) == len(outputs)
sorted_output = sorted(outputs, key=lambda x: x.value)
for i, j in zip(sorted_input, sorted_output):
assert i == j
program_runner = TaskProgramRunner(
n, t, {MixinConstants.MultiplyShareArray: BeaverMultiplyArrays()})
program_runner.add(verify_output, k=k, delta=delta)
await program_runner.join()
def get_dkg_setup_commands(s3manager, instance_ids):
from honeybadgermpc.preprocessing import PreProcessedElements
from honeybadgermpc.preprocessing import PreProcessingConstants as Constants
n, t = AwsConfig.TOTAL_VM_COUNT, AwsConfig.MPC_CONFIG.T
logging.info("Starting to create preprocessing files.")
stime = time()
pp_elements = PreProcessedElements()
pp_elements.generate_triples(600, n, t)
pp_elements.generate_rands(600, n, t)
logging.info(f"Preprocessing files created in {time()-stime}")
setup_commands = []
total_time = 0
logging.info(f"Uploading input files to AWS S3.")
stime = time()
triple_urls = s3manager.upload_files(
[build_file_name_triple(n, t, i) for i in range(n)])
input_urls = s3manager.upload_files(
[build_file_name_rand(n, t, i) for i in range(n)])
logging.info(f"Inputs successfully uploaded in {time()-stime} seconds.")
setup_commands = [[
instance_id,
[
"sudo docker pull %s" % (AwsConfig.DOCKER_IMAGE_PATH),
"mkdir -p sharedata",
"cd sharedata; curl -sSO %s" % (triple_urls[i]),
"cd sharedata; curl -sSO %s" % (input_urls[i]),
"mkdir -p benchmark-logs",
],
] for i, instance_id in enumerate(instance_ids)]
return setup_commands
async def prog():
n, t = 4, 1
pp = FakePreProcessedElements()
pp.generate_zeros(1000, n, t)
pp.generate_triples(120000, n, t)
pp.generate_share_bits(1000, n, t)
pp.generate_bits(3000, n, t)
pp.generate_rands(10000, n, t)
program_runner = TaskProgramRunner(n, t, config)
program_runner.add(laesa_test_1)
results = await program_runner.join()
return results
def get_powermixing_setup_commands(max_k, runid, s3manager, instance_ids):
from honeybadgermpc.preprocessing import PreProcessedElements
from honeybadgermpc.preprocessing import PreProcessingConstants as Constants
n, t = AwsConfig.TOTAL_VM_COUNT, AwsConfig.MPC_CONFIG.T
k = max_k if max_k else AwsConfig.MPC_CONFIG.K
logging.info("Starting to create preprocessing files.")
stime = time()
pp_elements = PreProcessedElements()
pp_elements.generate_powers(k, n, t, k)
pp_elements.generate_rands(k, n, t)
logging.info(f"Preprocessing files created in {time()-stime}")
setup_commands = []
total_time = 0
logging.info(f"Uploading input files to AWS S3.")
for i, instance_id in enumerate(instance_ids):
url = s3manager.upload_file(f"aws/download_input.sh")
commands = [
"sudo docker pull %s" % (AwsConfig.DOCKER_IMAGE_PATH),
f"curl -sSO {url}",
"mkdir -p sharedata",
"cp download_input.sh sharedata/download_input.sh ",
"mkdir -p benchmark-logs",
"ulimit -n 10000",
]
file_names = []
for j in range(k):
prefix1 = f"{pp_elements.mixins[Constants.POWERS].file_prefix}_{j}"
file_names.append(
pp_elements.mixins[Constants.POWERS].build_filename(
n, t, i, prefix=prefix1))
file_names.append(
pp_elements.mixins[Constants.RANDS].build_filename(n, t, i))
stime = time()
urls = s3manager.upload_files(file_names)
total_time += time() - stime
with open("%s-%d-links" % (runid, i), "w") as f:
for url in urls:
print(url, file=f)
fname = f"{runid}-{i}-links"
url = s3manager.upload_file(fname)
commands.append(
f"cd sharedata; curl -sSO {url}; bash download_input.sh {fname}")
setup_commands.append([instance_id, commands])
logging.info(f"Upload completed in {total_time} seconds.")
return setup_commands
async def test_get_rand():
n, t = 4, 1
num_rands = 2
pp_elements = PreProcessedElements()
pp_elements.generate_rands(1000, n, t)
async def _prog(ctx):
for _ in range(num_rands):
# Nothing to assert here, just check if the
# required number of rands are generated
ctx.preproc.get_rand(ctx)
program_runner = TaskProgramRunner(n, t)
program_runner.add(_prog)
await program_runner.join()
def get_butterfly_network_setup_commands(max_k, s3manager, instance_ids):
from honeybadgermpc.preprocessing import PreProcessedElements
from honeybadgermpc.preprocessing import PreProcessingConstants as Constants
n, t = AwsConfig.TOTAL_VM_COUNT, AwsConfig.MPC_CONFIG.T
k = max_k if max_k else AwsConfig.MPC_CONFIG.K
logging.info("Starting to create preprocessing files.")
stime = time()
num_switches = k * int(log(k, 2))**2
pp_elements = PreProcessedElements()
pp_elements.generate_triples(2 * num_switches, n, t)
pp_elements.generate_one_minus_ones(num_switches, n, t)
pp_elements.generate_rands(k, n, t)
logging.info(f"Preprocessing files created in {time()-stime}")
logging.info("Uploading inputs to AWS S3.")
stime = time()
triple_urls = s3manager.upload_files([
pp_elements.mixins[Constants.TRIPLES]._build_file_name(n, t, i)
for i in range(n)
])
input_urls = s3manager.upload_files([
pp_elements.mixins[Constants.RANDS]._build_file_name(n, t, i)
for i in range(n)
])
rand_share_urls = s3manager.upload_files([
pp_elements.mixins[Constants.ONE_MINUS_ONE]._build_file_name(n, t, i)
for i in range(n)
])
logging.info(f"Inputs successfully uploaded in {time()-stime} seconds.")
setup_commands = [[
instance_id,
[
"sudo docker pull %s" % (AwsConfig.DOCKER_IMAGE_PATH),
"mkdir -p sharedata",
"cd sharedata; curl -sSO %s" % (triple_urls[i]),
"cd sharedata; curl -sSO %s" % (rand_share_urls[i]),
"cd sharedata; curl -sSO %s" % (input_urls[i]),
"mkdir -p benchmark-logs",
],
] for i, instance_id in enumerate(instance_ids)]
return setup_commands
async def test_degree_reduction_share_array(test_runner):
n, t = 7, 2
pp_elements = PreProcessedElements()
pp_elements.generate_rands(1000, n, 2 * t)
pp_elements.generate_double_shares(1000, n, t)
async def _prog(context):
shares = [context.preproc.get_rand(context, 2 * t) for _ in range(10)]
sh_x_2t = context.ShareArray(shares, 2 * t)
x_actual = await (
await DoubleSharingMultiplyArrays.reduce_degree_share_array(
context, sh_x_2t)).open()
x_expected = await sh_x_2t.open()
for a, b in zip(x_actual, x_expected):
assert a == b
await run_test_program(_prog, test_runner, n, t)
async def test_asynchronous_mixing():
import asyncio
import apps.asynchromix.powermixing as pm
from honeybadgermpc.mpc import TaskProgramRunner
n, t, k = 3, 1, 4
pp_elements = PreProcessedElements()
pp_elements.generate_powers(k, n, t, k)
pp_elements.generate_rands(1000, n, t)
async def verify_output(context, **kwargs):
result, input_shares = kwargs["result"], kwargs["input_shares"]
my_shares = input_shares[context.myid]
assert len(result) == len(my_shares)
inputs = await asyncio.gather(
*[context.Share(sh.v, t).open() for sh in my_shares])
assert sorted(map(lambda x: x.value, inputs)) == sorted(result)
result, input_shares = await pm.async_mixing(n, t, k)
program_runner = TaskProgramRunner(n, t)
program_runner.add(verify_output, result=result, input_shares=input_shares)
await program_runner.join()
def _preprocess(n, t, k, to_generate):
from honeybadgermpc.preprocessing import PreProcessedElements
pp_elements = PreProcessedElements()
for kind in to_generate:
if kind == "triples":
pp_elements.generate_triples(k, n, t)
elif kind == "cubes":
pp_elements.generate_cubes(k, n, t)
elif kind == "zeros":
pp_elements.generate_zeros(k, n, t)
elif kind == "rands":
pp_elements.generate_rands(k, n, t)
elif kind == "bits":
pp_elements.generate_bits(k, n, t)
elif kind == "one_minus_one":
pp_elements.generate_one_minus_ones(k, n, t)
elif kind == "double_shares":
pp_elements.generate_double_shares(k, n, t)
elif kind == "share_bits":
pp_elements.generate_share_bits(k, n, t)
else:
raise ValueError(f"{kind} must be manually preprocessed")
k = int(HbmpcConfig.extras["k"])
pp_elements = PreProcessedElements()
pp_elements.clear_preprocessing()
asyncio.set_event_loop(asyncio.new_event_loop())
loop = asyncio.get_event_loop()
try:
if not HbmpcConfig.skip_preprocessing:
# Need to keep these fixed when running on processes.
field = GF(Subgroup.BLS12_381)
a_s = [field(i) for i in range(1000 + k, 1000, -1)]
if HbmpcConfig.my_id == 0:
pp_elements.generate_rands(k, HbmpcConfig.N, HbmpcConfig.t)
pp_elements.generate_powers(k, HbmpcConfig.N, HbmpcConfig.t, k)
pp_elements.preprocessing_done()
else:
loop.run_until_complete(pp_elements.wait_for_preprocessing())
loop.run_until_complete(
async_mixing_in_processes(
HbmpcConfig.peers,
HbmpcConfig.N,
HbmpcConfig.t,
k,
run_id,
HbmpcConfig.my_id,
))
finally:
