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#!/usr/bin/env python
# sp800_22_non_overlapping_template_matching_test.py
#
# Copyright (C) 2017 David Johnston
# This program is distributed under the terms of the GNU General Public License.
#
# This file is part of sp800_22_tests.
#
# sp800_22_tests is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# sp800_22_tests is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with sp800_22_tests. If not, see <http://www.gnu.org/licenses/>.
from __future__ import print_function
import math
#from scipy.special import gamma, gammainc, gammaincc
from gamma_functions import *
import random
def non_overlapping_template_matching_test(bits):
# The templates provdided in SP800-22rev1a
templates = [None for x in range(7)]
templates[0] = [[0,1],[1,0]]
templates[1] = [[0,0,1],[0,1,1],[1,0,0],[1,1,0]]
templates[2] = [[0,0,0,1],[0,0,1,1],[0,1,1,1],[1,0,0,0],[1,1,0,0],[1,1,1,0]]
templates[3] = [[0,0,0,0,1],[0,0,0,1,1],[0,0,1,0,1],[0,1,0,1,1],[0,0,1,1,1],[0,1,1,1,1],
[1,1,1,0,0],[1,1,0,1,0],[1,0,1,0,0],[1,1,0,0,0],[1,0,0,0,0],[1,1,1,1,0]]
templates[4] = [[0,0,0,0,0,1],[0,0,0,0,1,1],[0,0,0,1,0,1],[0,0,0,1,1,1],[0,0,1,0,1,1],
[0,0,1,1,0,1],[0,0,1,1,1,1],[0,1,0,0,1,1],
[0,1,0,1,1,1],[0,1,1,1,1,1],[1,0,0,0,0,0],
[1,0,1,0,0,0],[1,0,1,1,0,0],[1,1,0,0,0,0],
[1,1,0,0,1,0],[1,1,0,1,0,0],[1,1,1,0,0,0],
[1,1,1,0,1,0],[1,1,1,1,0,0],[1,1,1,1,1,0]]
templates[5] = [[0,0,0,0,0,0,1],[0,0,0,0,0,1,1],[0,0,0,0,1,0,1],[0,0,0,0,1,1,1],
[0,0,0,1,0,0,1],[0,0,0,1,0,1,1],[0,0,0,1,1,0,1],[0,0,0,1,1,1,1],
[0,0,1,0,0,1,1],[0,0,1,0,1,0,1],[0,0,1,0,1,1,1],[0,0,1,1,0,1,1],
[0,0,1,1,1,0,1],[0,0,1,1,1,1,1],[0,1,0,0,0,1,1],[0,1,0,0,1,1,1],
[0,1,0,1,0,1,1],[0,1,0,1,1,1,1],[0,1,1,0,1,1,1],[0,1,1,1,1,1,1],
[1,0,0,0,0,0,0],[1,0,0,1,0,0,0],[1,0,1,0,0,0,0],[1,0,1,0,1,0,0],
[1,0,1,1,0,0,0],[1,0,1,1,1,0,0],[1,1,0,0,0,0,0],[1,1,0,0,0,1,0],
[1,1,0,0,1,0,0],[1,1,0,1,0,0,0],[1,1,0,1,0,1,0],[1,1,0,1,1,0,0],
[1,1,1,0,0,0,0],[1,1,1,0,0,1,0],[1,1,1,0,1,0,0],[1,1,1,0,1,1,0],
[1,1,1,1,0,0,0],[1,1,1,1,0,1,0],[1,1,1,1,1,0,0],[1,1,1,1,1,1,0]]
templates[6] = [[0,0,0,0,0,0,0,1],[0,0,0,0,0,0,1,1],[0,0,0,0,0,1,0,1],[0,0,0,0,0,1,1,1],
[0,0,0,0,1,0,0,1],[0,0,0,0,1,0,1,1],[0,0,0,0,1,1,0,1],[0,0,0,0,1,1,1,1],
[0,0,0,1,0,0,1,1],[0,0,0,1,0,1,0,1],[0,0,0,1,0,1,1,1],[0,0,0,1,1,0,0,1],
[0,0,0,1,1,0,1,1],[0,0,0,1,1,1,0,1],[0,0,0,1,1,1,1,1],[0,0,1,0,0,0,1,1],
[0,0,1,0,0,1,0,1],[0,0,1,0,0,1,1,1],[0,0,1,0,1,0,1,1],[0,0,1,0,1,1,0,1],
[0,0,1,0,1,1,1,1],[0,0,1,1,0,1,0,1],[0,0,1,1,0,1,1,1],[0,0,1,1,1,0,1,1],
[0,0,1,1,1,1,0,1],[0,0,1,1,1,1,1,1],[0,1,0,0,0,0,1,1],[0,1,0,0,0,1,1,1],
[0,1,0,0,1,0,1,1],[0,1,0,0,1,1,1,1],[0,1,0,1,0,0,1,1],[0,1,0,1,0,1,1,1],
[0,1,0,1,1,0,1,1],[0,1,0,1,1,1,1,1],[0,1,1,0,0,1,1,1],[0,1,1,0,1,1,1,1],
[0,1,1,1,1,1,1,1],[1,0,0,0,0,0,0,0],[1,0,0,1,0,0,0,0],[1,0,0,1,1,0,0,0],
[1,0,1,0,0,0,0,0],[1,0,1,0,0,1,0,0],[1,0,1,0,1,0,0,0],[1,0,1,0,1,1,0,0],
[1,0,1,1,0,0,0,0],[1,0,1,1,0,1,0,0],[1,0,1,1,1,0,0,0],[1,0,1,1,1,1,0,0],
[1,1,0,0,0,0,0,0],[1,1,0,0,0,0,1,0],[1,1,0,0,0,1,0,0],[1,1,0,0,1,0,0,0],
[1,1,0,0,1,0,1,0],[1,1,0,1,0,0,0,0],[1,1,0,1,0,0,1,0],[1,1,0,1,0,1,0,0],
[1,1,0,1,1,0,0,0],[1,1,0,1,1,0,1,0],[1,1,0,1,1,1,0,0],[1,1,1,0,0,0,0,0],
[1,1,1,0,0,0,1,0],[1,1,1,0,0,1,0,0],[1,1,1,0,0,1,1,0],[1,1,1,0,1,0,0,0],
[1,1,1,0,1,0,1,0],[1,1,1,0,1,1,0,0],[1,1,1,1,0,0,0,0],[1,1,1,1,0,0,1,0],
[1,1,1,1,0,1,0,0],[1,1,1,1,0,1,1,0],[1,1,1,1,1,0,0,0],[1,1,1,1,1,0,1,0],
[1,1,1,1,1,1,0,0],[1,1,1,1,1,1,1,0]]
n = len(bits)
# Choose the template B
r = random.SystemRandom()
template_list = r.choice(templates)
B = r.choice(template_list)
m = len(B)
N = 8
M = int(math.floor(len(bits)/8))
n = M*N
blocks = list() # Split into N blocks of M bits
for i in range(N):
blocks.append(bits[i*M:(i+1)*M])
W=list() # Count the number of matches of the template in each block Wj
for block in blocks:
position = 0
count = 0
while position < (M-m):
if block[position:position+m] == B:
position += m
count += 1
else:
position += 1
W.append(count)
mu = float(M-m+1)/float(2**m) # Compute mu and sigma
sigma = M * ((1.0/float(2**m))-(float((2*m)-1)/float(2**(2*m))))
chisq = 0.0 # Compute Chi-Square
for j in range(N):
chisq += ((W[j] - mu)**2)/(sigma**2)
p = gammaincc(N/2.0, chisq/2.0) # Compute P value
success = ( p >= 0.01)
return (success,p,None)
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