def test_nonlinear_function9():
for key_byte in range(256):
data = bytearray(16)
key = bytearray(15)
key.append(key_byte)
sbox = bytearray()
for byte in range(256):
data[-1] = byte
nonlinear_function9(data, key)
sbox.append(data[-2])
print find_best_differential(sbox)
print calculate_linearity(sbox)
def test_nonlinear_function9():
for key_byte in range(256):
data = bytearray(16)
key = bytearray(15)
key.append(key_byte)
sbox = bytearray()
for byte in range(256):
data[-1] = byte
nonlinear_function9(data, key)
sbox.append(data[-2])
print find_best_differential(sbox)
print calculate_linearity(sbox)
def test_function():
sbox = bytearray(256)
for x in range(256):
temp = x * x
sbox[x] = (temp >> 8) ^ (temp & 255)
print "Best differential: ", find_best_differential(sbox)
print "Linearity: ", calculate_linearity(sbox)
def test_function():
sbox = bytearray(256)
for x in range(256):
temp = x * x
sbox[x] = (temp >> 8) ^ (temp & 255)
print "Best differential: ", find_best_differential(sbox)
print "Linearity: ", calculate_linearity(sbox)
def test_generate_key():
# sbox = []
# for byte in range(256):
# data = bytearray(16)
# data[-2] = byte
# sbox.append(generate_key(data))
# print bytearray(sbox)
# print find_best_differential(sbox)
sbox = []
for byte in range(256):
data = bytearray(16)
data[-1] = byte
prf(data, generate_key(data))
sbox.append(data[-1])
print find_best_differential(sbox)
print calculate_linearity(sbox)
def test_generate_key():
# sbox = []
# for byte in range(256):
# data = bytearray(16)
# data[-2] = byte
# sbox.append(generate_key(data))
# print bytearray(sbox)
# print find_best_differential(sbox)
sbox = []
for byte in range(256):
data = bytearray(16)
data[-1] = byte
prf(data, generate_key(data))
sbox.append(data[-1])
print find_best_differential(sbox)
print calculate_linearity(sbox)
def test_speck():
for key in (pow(251, x, 257) % 256 for x in range(256)):
for left in range(256):
sbox = bytearray()
for right in range(256):
left, right = speck_round(left, right, key)
sbox.append(left & 255)
differentials = find_best_differential(sbox)
linearity = calculate_linearity(sbox)
print differentials
print linearity
def test_speck():
for key in (pow(251, x, 257) % 256 for x in range(256)):
for left in range(256):
sbox = bytearray()
for right in range(256):
left, right = speck_round(left, right, key)
sbox.append(left & 255)
differentials = find_best_differential(sbox)
linearity = calculate_linearity(sbox)
print differentials
print linearity
def test_nonlinear_function8():
#for _rotation in range(20):
# print "\nRotation: ", _rotation
_rotation = 5
for key in (pow(251, x, 257) % 256 for x in range(1, 16)):
sbox = bytearray()
for right in range(256):
left = 0
left, right = nonlinear_function8(left, right, key, _rotation=_rotation)
sbox.append(left >> 56)
differentials = find_best_differential(sbox)
linearity = calculate_linearity(sbox)
print differentials
print linearity
def test_nonlinear_function8():
#for _rotation in range(20):
# print "\nRotation: ", _rotation
_rotation = 5
for key in (pow(251, x, 257) % 256 for x in range(1, 16)):
sbox = bytearray()
for right in range(256):
left = 0
left, right = nonlinear_function8(left, right, key, _rotation=_rotation)
sbox.append(left >> 56)
differentials = find_best_differential(sbox)
linearity = calculate_linearity(sbox)
print differentials
print linearity
def test_prp_s_box():
import collections
s_box = collections.defaultdict(bytearray)
rounds = 4
for ending in range(256):
data = bytearray(16)
data[-1] = ending
for round in range(rounds):
prp(data, xor_sum(data))
s_box[round].append(data[-2])
from differential import find_best_differential
from linear import calculate_linearity
for round in range(rounds):
_s_box = s_box[round]
print "Best differential after {} rounds: ".format(round + 1), find_best_differential(_s_box)
print "Linearity after {} rounds: ".format(round + 1), calculate_linearity(_s_box)
def test_prp_s_box():
import collections
s_box = collections.defaultdict(bytearray)
rounds = 4
for ending in range(256):
data = bytearray(16)
data[-1] = ending
for round in range(rounds):
prp(data, xor_sum(data))
s_box[round].append(data[-2])
from differential import find_best_differential
from linear import calculate_linearity
for round in range(rounds):
_s_box = s_box[round]
print "Best differential after {} rounds: ".format(
round + 1), find_best_differential(_s_box)
print "Linearity after {} rounds: ".format(
round + 1), calculate_linearity(_s_box)
import os
from differential import find_best_differential
from linear import calculate_linearity
def shuffle(array, key):
for index in reversed(range(1, len(array))):
other_index = key[index] & (index - 1)
array[index], array[other_index] = array[other_index], array[index]
for x in range(16):
sbox = bytearray(range(256))
key = bytearray(os.urandom(256))
shuffle(sbox, key)
key = bytearray(os.urandom(256))
shuffle(sbox, key)
shuffle(sbox, key)
print find_best_differential(sbox)
print calculate_linearity(sbox)
def cryptanalyze_sbox_worst_case(sbox,
differential_types=STANDARD_DIFFERENTIAL):
differentials = differential.find_best_differential(
sbox, differential_types)
linearity = linear.calculate_linearity(sbox, log(len(sbox), 2))
return differentials, linearity
def test_random_sbox():
for x in range(16):
sbox = bytearray(os.urandom(256))
print find_best_differential(sbox)
print calculate_linearity(sbox)
import os
from differential import find_best_differential
from linear import calculate_linearity
def shuffle(array, key):
for index in reversed(range(1, len(array))):
other_index = key[index] & (index - 1)
array[index], array[other_index] = array[other_index], array[index]
for x in range(16):
sbox = bytearray(range(256))
key = bytearray(os.urandom(256))
shuffle(sbox, key)
key = bytearray(os.urandom(256))
shuffle(sbox, key)
shuffle(sbox, key)
print find_best_differential(sbox)
print calculate_linearity(sbox)
def test_random_sbox():
for x in range(16):
sbox = bytearray(os.urandom(256))
print find_best_differential(sbox)
print calculate_linearity(sbox)
def cryptanalyze_sbox_worst_case(sbox, differential_types=STANDARD_DIFFERENTIAL):
differentials = differential.find_best_differential(sbox, differential_types)
linearity = linear.calculate_linearity(sbox, log(len(sbox), 2))
return differentials, linearity