flag = 3 if S_array[iterate] - lol < S_array[temp3]: temp = theta[S_array[temp3]]; theta[S_array[temp3]] = theta[S_array[i]]; theta[S_array[iterate]] = temp; flag = 2 i = i+1 print theta print flag print test.value_nonl(theta) # print temp
# empty_array[i] = int(math.floor(empty_array[i]))
# for i in range(256):
# count = empty_array.count[i]
# for j in range(i):
length = len(empty_array)
# print length
print empty_array
print is_bijective(empty_array)
print test.value_nonl(empty_array)
#print('the random number is',x)
#x=81;
# for iterate in range(user_iter):
# t = theta[node] + nutrientsfunc(theta,flag,node,last);
# f = theta[node+x] + nutrientsfunc(theta,flag,node+x,last);
# diffrence = f - t;
# # iterate = iterate + 1;
# count = empty_array.count[i]
# for j in range(i):
length = len(empty_array)
# print length
print empty_array
print is_bijective(empty_array)
print test.value_nonl(empty_array)
#print('the random number is',x)
#x=81;
# for iterate in range(user_iter):
# t = theta[node] + nutrientsfunc(theta,flag,node,last);
# f = theta[node+x] + nutrientsfunc(theta,flag,node+x,last);
# diffrence = f - t;
# # iterate = iterate + 1;
# List of Columns
p = "\nS-BOX "
for i in range(16):
p += "%02x" % i + " "
p += "\n"
for i in range(70):
p += "-"
p += "\n"
# Row
for i in range(16):
p += "%02x" % i + " | "
# Entries
for j in range(16):
p += "%02x" % sbox[16 * i + j] + " "
p += "\n"
return p.upper()
if __name__ == "__main__":
print("Initial Sbox is : ")
print(pretty(gen()))
print("Is initial Sbox bijective:", is_bijective(gen()))
print("Nonlinearity of Initial Sbox:", value_nonl(gen()))
---------
set_Vertices : set
A set of vertices of graph.
node : int
The vertex to which we need minimum cost.
"""
cost_path = 0
for node in range(len(set_Vertices)-1):
cost_path += dist(graph, set_Vertices[node], set_Vertices[node+1])
return cost_path
if __name__ == '__main__':
graphs = []
initial_non = value_nonl(gen())
# dict conatining sbox
non_sbox = {initial_non: gen()}
all_perms = list(per(range(8)))
array = gen()
if is_bijective(array):
for var in range(10):
array_mod = []
for num in range(32):
array_mod, graph = substitution(
all_perms, array, array_mod, num)
graphs.append(graph)
# calculate non-linearity of modified Sbox
nn_array_mod = value_nonl(array_mod)
if nn_array_mod > limit1:
non_sbox[nn_array_mod] = [array_mod, graphs]
import math
import random
from random import randint
import test
threshold = 0;
flag = 0;
flag1 = 0;
last =255;
theta = [205, 78, 47, 165, 239, 178, 9, 175, 233, 123, 251, 216, 58, 26, 96, 199, 220, 15, 206, 83, 154, 235, 143, 245, 64, 79, 210, 63, 42, 82, 69, 134, 111, 50, 227, 229, 159, 156, 160, 145, 197, 124, 72, 228, 55, 77, 2, 189, 10, 18, 209, 122, 100, 20, 226, 129, 34, 37, 137, 200, 31, 240, 242, 62, 87, 136, 91, 59, 7, 106, 90, 135, 198, 27, 179, 158, 139, 241, 138, 144, 104, 211, 97, 148, 19, 108, 125, 192, 118, 46, 230, 12, 109, 161, 195, 221, 93, 246, 248, 196, 99, 225, 52, 120, 49, 188, 73, 67, 238, 207, 119, 163, 232, 43, 35, 254, 215, 21, 126, 127, 113, 41, 61, 75, 94, 172, 141, 89, 71, 219, 110, 45, 150, 234, 36, 112, 171, 131, 11, 237, 102, 32, 250, 54, 208, 4, 213, 29, 180, 243, 168, 60, 169, 201, 214, 13, 114, 116, 223, 23, 244, 185, 181, 84, 190, 247, 53, 28, 255, 6, 193, 253, 149, 167, 202, 17, 66, 22, 57, 191, 186, 44, 130, 14, 170, 1, 81, 105, 48, 88, 236, 155, 95, 25, 152, 166, 252, 38, 217, 5, 0, 157, 65, 176, 16, 140, 103, 76, 40, 121, 249, 173, 218, 24, 115, 183, 147, 68, 153, 231, 142, 3, 224, 187, 107, 177, 86, 51, 146, 132, 74, 133, 212, 56, 164, 174, 98, 203, 182, 30, 70, 39, 117, 80, 128, 33, 184, 8, 85, 222, 162, 194, 204, 151, 101, 92]
non_li = test.value_nonl(theta)
print non_li
fo = open("substitution.txt", "wb")
iterate = 0;
def nutrientsfunc(theta,flag,first,last):
i = 0
if flag==1:
J=0;
else:
