mirror of
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99 lines
2.5 KiB
Python
99 lines
2.5 KiB
Python
import numpy as np
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from sage.all import save, load, ceil
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def sort_data(security_level):
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from operator import itemgetter
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# step 1. load the data
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X = load("{}.sobj".format(security_level))
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# step 2. sort by SD
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x = sorted(X["{}".format(security_level)], key=itemgetter(2))
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# step3. replace the sorted value
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X["{}".format(security_level)] = x
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return X
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def generate_curve(security_level):
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# step 1. get the data
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X = sort_data(security_level)
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# step 2. group the n and sigma data into lists
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N = []
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SD = []
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for x in X["{}".format(security_level)]:
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N.append(x[0])
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SD.append(x[2] + 0.5)
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# step 3. perform interpolation and return coefficients
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(a, b) = np.polyfit(N, SD, 1)
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return a, b
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def verify_curve(security_level, a=None, b=None):
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# step 1. get the table and max values of n, sd
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X = sort_data(security_level)
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n_max = X["{}".format(security_level)][0][0]
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sd_max = X["{}".format(security_level)][-1][2]
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# step 2. a function to get model values
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def f_model(a, b, n):
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return ceil(a * n + b)
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# step 3. a function to get table values
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def f_table(table, n):
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for i in range(len(table)):
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n_val = table[i][0]
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if n < n_val:
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pass
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else:
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j = i
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break
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# now j is the correct index, we return the corresponding sd
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return table[j][2]
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# step 3. for each n, check whether we satisfy the table
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n_min = max(2 * security_level, 450, X["{}".format(security_level)][-1][0])
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print(n_min)
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print(n_max)
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for n in range(n_max, n_min, - 1):
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model_sd = f_model(a, b, n)
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table_sd = f_table(X["{}".format(security_level)], n)
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print(n, table_sd, model_sd, model_sd >= table_sd)
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if table_sd > model_sd:
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print("MODEL FAILS at n = {}".format(n))
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return "FAIL"
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return "PASS", n_min
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def generate_and_verify(security_levels, log_q, name="verified_curves"):
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data = []
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for sec in security_levels:
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print("WE GO FOR {}".format(sec))
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# generate the model for security level sec
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(a_sec, b_sec) = generate_curve(sec)
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# verify the model for security level sec
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res = verify_curve(sec, a_sec, b_sec)
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# append the information into a list
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data.append((a_sec, b_sec - log_q, sec, res[0], res[1]))
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save(data, "{}.sobj".format(name))
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return data
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data = generate_and_verify(
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[80, 96, 112, 128, 144, 160, 176, 192, 256], log_q=64)
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print(data)
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