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allow for a single arg for AWS

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Ben
2022-04-11 15:11:03 +01:00
parent f18b7c2a55
commit d0efc71796
1 changed files with 15 additions and 4 deletions
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19
new_scripts.py
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@@ -2,6 +2,7 @@ from estimator_new import *
from sage.all import oo, save
from math import log2
def old_models(security_level, sd, logq = 32):
"""
Use the old model as a starting point for the data gathering step
@@ -142,7 +143,7 @@ def automated_param_select_n(params, target_security=128):
return params
def generate_parameter_matrix(params_in, sd_range, target_security_levels=[128]):
def generate_parameter_matrix(params_in, sd_range, target_security_levels=[128], name="v0.sobj"):
"""
:param sd_range: a tuple (sd_min, sd_max) giving the values of sd for which to generate parameters
:param params: the standard deviation of the LWE error
@@ -164,16 +165,26 @@ def generate_parameter_matrix(params_in, sd_range, target_security_levels=[128])
Xe_new = nd.NoiseDistribution.DiscreteGaussian(2**sd)
params_out = automated_param_select_n(params_in.updated(Xe=Xe_new), target_security=lam)
results["{}".format(lam)].append((params_out.n, params_out.q, params_out.Xe.stddev))
save(results, "{}.sobj".format(name))
return results
def generate_zama_curves64(sd_range=[2, 60], target_security_levels=[128, 192, 256]):
def generate_zama_curves64(sd_range=[2, 60], target_security_levels=[256], name="v0256.sobj"):
D = ND.DiscreteGaussian
init_params = LWE.Parameters(n=1024, q=2 ** 64, Xs=D(0.50, -0.50), Xe=D(131072.00), m=oo, tag='TFHE_DEFAULT')
raw_data = generate_parameter_matrix(init_params, sd_range=sd_range, target_security_levels=target_security_levels)
raw_data = generate_parameter_matrix(init_params, sd_range=sd_range, target_security_levels=target_security_levels, name=name)
return raw_data
generate_zama_curves64()
def plota_curve(raw_data, security_level):
data = raw_data["{}".format(security_level)]
import sys
a = int(sys.argv[1])
print(a)
generate_zama_curves64(target_security_levels=[a])