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129 lines
4.1 KiB
Python
129 lines
4.1 KiB
Python
import estimator.estimator as est
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from concrete_params import concrete_LWE_params, concrete_RLWE_params
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from hybrid_decoding import parameter_search
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def get_all_security_levels(params):
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""" A function which gets the security levels of a collection of TFHE parameters,
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using the four cost models: classical, quantum, classical_conservative, and
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quantum_conservative
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:param params: a dictionary of LWE parameter sets (see concrete_params)
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EXAMPLE:
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sage: X = get_all_security_levels(concrete_LWE_params)
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sage: X
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[['LWE128_256',
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126.692189756144,
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117.566189756144,
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98.6960000000000,
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89.5700000000000], ...]
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"""
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RESULTS = []
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for param in params:
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results = [param]
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x = params["{}".format(param)]
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n = x["n"] * x["k"]
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q = 2 ** 32
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sd = 2 ** (x["sd"]) * q
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alpha = sqrt(2 * pi) * sd / RR(q)
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secret_distribution = (0, 1)
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# assume access to an infinite number of samples
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m = oo
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for model in cost_models:
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try:
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model = model[0]
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except:
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model = model
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estimate = parameter_search(mitm = True, reduction_cost_model = est.BKZ.sieve, n = n, q = q, alpha = alpha, m = m, secret_distribution = secret_distribution)
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results.append(get_security_level(estimate))
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RESULTS.append(results)
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return RESULTS
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def get_hybrid_security_levels(params):
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""" A function which gets the security levels of a collection of TFHE parameters,
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using the four cost models: classical, quantum, classical_conservative, and
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quantum_conservative
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:param params: a dictionary of LWE parameter sets (see concrete_params)
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EXAMPLE:
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sage: X = get_all_security_levels(concrete_LWE_params)
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sage: X
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[['LWE128_256',
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126.692189756144,
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117.566189756144,
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98.6960000000000,
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89.5700000000000], ...]
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"""
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RESULTS = []
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for param in params:
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results = [param]
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x = params["{}".format(param)]
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n = x["n"] * x["k"]
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q = 2 ** 32
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sd = 2 ** (x["sd"]) * q
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alpha = sqrt(2 * pi) * sd / RR(q)
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secret_distribution = (0, 1)
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# assume access to an infinite number of papers
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m = oo
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model = est.BKZ.sieve
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estimate = parameter_search(mitm = True, reduction_cost_model = est.BKZ.sieve, n = n, q = q, alpha = alpha, m = m, secret_distribution = secret_distribution)
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results.append(get_security_level(estimate))
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RESULTS.append(results)
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return RESULTS
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def latexit(results):
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"""
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A function which takes the output of get_all_security_levels() and
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turns it into a latex table
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:param results: the security levels
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sage: X = get_all_security_levels(concrete_LWE_params)
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sage: latextit(X)
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\begin{tabular}{llllll}
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LWE128_256 & $126.69$ & $117.57$ & $98.7$ & $89.57$ & $217.55$ \\
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LWE128_512 & $135.77$ & $125.92$ & $106.58$ & $96.73$ & $218.53$ \\
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LWE128_638 & $135.27$ & $125.49$ & $105.7$ & $95.93$ & $216.81$ \\
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[...]
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"""
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return latex(table(results))
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def markdownit(results, headings = ["Parameter Set", "Classical", "Quantum", "Classical (c)", "Quantum (c)", "Enum"]):
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"""
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A function which takes the output of get_all_security_levels() and
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turns it into a markdown table
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:param results: the security levels
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sage: X = get_all_security_levels(concrete_LWE_params)
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sage: markdownit(X)
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# estimates
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|Parameter Set|Classical|Quantum|Classical (c)|Quantum (c)| Enum |
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|-------------|---------|-------|-------------|-----------|------|
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|LWE128_256 |126.69 |117.57 |98.7 |89.57 |217.55|
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|LWE128_512 |135.77 |125.92 |106.58 |96.73 |218.53|
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|LWE128_638 |135.27 |125.49 |105.7 |95.93 |216.81|
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[...]
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"""
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writer = MarkdownTableWriter(value_matrix = results, headers = headings, table_name = "estimates")
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writer.write_table()
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return writer
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# dual bug example
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# n = 256; q = 2**32; sd = 2**(-4); reduction_cost_model = BKZ.sieve
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# _ = estimate_lwe(n, alpha, q, reduction_cost_model) |