def decode(out):
Add= lambda x,y : F.Add(x,y)
Mul = lambda x,y: F.Multiply(x,y)
Sub = lambda x,y: F.Subtract(x,y)
Div = lambda x,y: divi(x,y)
m = genericmatrix.GenericMatrix(size=(8,8),zeroElement=0,identityElement=1,add=Add,mul=Mul,sub=Sub,div=Div)
for i in range(8):
m.SetRow(i,keys[i])
output=[]
for i in range(16):
output.append((ord(out[2*i])-ord('f'))*16+(ord(out[2*i+1])-ord('f')))
print(output)
# keys_inv=[[keys[i][j] for j in range(8)] for i in range(8)]
# det=1
# for i in range(8):
# det=F.Multiply(det,keys[i][i])
# print(det)
# for i in range(8):
# for j in range(8):
# keys_inv[i][j]=div(keys[i][j],det)
keys_inv=m.Inverse()
print(keys_inv)
output[0:8]=inv_E(output[0:8])
output[0:8]=inv_A(output[0:8],keys_inv)
output[0:8]=inv_E(output[0:8])
output[0:8]=inv_A(output[0:8],keys_inv)
output[0:8]=inv_E(output[0:8])
output[8:16]=inv_E(output[8:16])
output[8:16]=inv_A(output[8:16],keys_inv)
output[8:16]=inv_E(output[8:16])
output[8:16]=inv_A(output[8:16],keys_inv)
output[8:16]=inv_E(output[8:16])
return output
def mix_column(input_state, mode):
# define GF(2^8) (i.e., GF(256)) field
F = ffield.FField(8)
# depending on the mode of operation get the right mix_column matrix
if mode == 'E':
column_matrix = genericmatrix.GenericMatrix(size=(4, 4),
add=F.Add,
sub=F.Subtract,
mul=F.Multiply,
div=F.Divide)
row = [2, 3, 1, 1]
for i in range(4):
column_matrix.SetRow(i, row)
row = rotate(row, -1)
elif mode == 'D':
column_matrix = genericmatrix.GenericMatrix(size=(4, 4),
add=F.Add,
sub=F.Subtract,
mul=F.Multiply,
div=F.Divide)
row = [14, 11, 13, 9]
for i in range(4):
column_matrix.SetRow(i, row)
row = rotate(row, -1)
else:
raise ValueError('invalid mode of operation, mode = {0}'.format(mode))
# convert input_state to input_matrix
input_matrix = reshape_as_matrix(input_state)
# perform matrix multiplication using * operator
output_matrix = input_matrix * column_matrix
# convert output_matrix to output_state
output_state = reshape_as_state(output_matrix)
return output_state
def reshape_as_matrix(input_state):
# define GF(2^8) (i.e., GF(256)) field
F = ffield.FField(8)
# define a matrix in GF(256)
output_matrix = genericmatrix.GenericMatrix(size=(4, 4),
add=F.Add,
sub=F.Subtract,
mul=F.Multiply,
div=F.Divide)
# add the corresponding elements from the input_state to the matrix
for i in range(4):
output_matrix.SetRow(i, input_state[i * 4:(i * 4) + 4])
return output_matrix
def genMatrix(size: tuple, min=0, max=P):
if not isinstance(size, tuple) or len(size) != 2:
raise Exception('Matrix size error')
v = genericmatrix.GenericMatrix(size,
zeroElement=0,
identityElement=1,
add=lambda x, y: (x + y) % P,
sub=lambda x, y: (x - y + P) % P,
mul=mymul,
div=lambda x, y:
(x * (_extended_gcd(y, P))) % P)
row, col = size
for r in range(row):
tempcol = [random.randint(min, max) for c in range(col)]
v.SetRow(r, tempcol)
return v
def invert_matrix():
field = ffield.FField(7, gen=0x83)
matrix = genericmatrix.GenericMatrix(size=(8, 8),
zeroElement=0,
identityElement=1,
add=field.Add,
mul=field.Multiply,
sub=field.Subtract,
div=field.Divide)
matrix.SetRow(0, [get_int_from_BV(i) for i in A_matrix[0]])
matrix.SetRow(1, [get_int_from_BV(i) for i in A_matrix[1]])
matrix.SetRow(2, [get_int_from_BV(i) for i in A_matrix[2]])
matrix.SetRow(3, [get_int_from_BV(i) for i in A_matrix[3]])
matrix.SetRow(4, [get_int_from_BV(i) for i in A_matrix[4]])
matrix.SetRow(5, [get_int_from_BV(i) for i in A_matrix[5]])
matrix.SetRow(6, [get_int_from_BV(i) for i in A_matrix[6]])
matrix.SetRow(7, [get_int_from_BV(i) for i in A_matrix[7]])
inverse = matrix.Inverse()
for rownum in range(8):
row = [bv(i) for i in inverse.GetRow(rownum)]
A_Inverse.append(row)
def xor(a, b):
assert (len(a) == len(b))
return "".join(["0" if a[i] == b[i] else "1" for i in range(len(a))])
""" Finite field operations """
GF = ffield.FField(5)
XOR = lambda x, y: x ^ y
MUL = lambda x, y: GF.Multiply(x, y)
DIV = lambda x, y: GF.Multiply(x, GF.Inverse(y))
m = genericmatrix.GenericMatrix(size=(3, 3),
zeroElement=0,
identityElement=1,
add=XOR,
mul=MUL,
sub=XOR,
div=DIV)
alpha = 2
m.SetRow(0, [1, 1, alpha])
m.SetRow(1, [1, alpha, 1])
m.SetRow(2, [alpha, 1, 1])
def round(data, key):
tmp = permutation(data)
tmp2 = ""
for i in range(0, 45, 5):
x = toInt(tmp[i:i + 5])
tmp2 += bin_format(GF.Inverse(x), 5)
Descripttion : cal x^-1 at GF(2^8) Version : from https://mp.weixin.qq.com/s/TsnPvdPOcgKguFZbhMDWQw Autor : one30: [email protected] Date : 2021-03-06 11:22:31 LastEditTime : 2021-03-06 14:31:35 FilePath : /cal_aes_x_inverse.py ''' from pyfinite import genericmatrix XOR = lambda x, y: x ^ y AND = lambda x, y: x & y DIV = lambda x, y: x m = genericmatrix.GenericMatrix(size=(8, 8), zeroElement=0, identityElement=1, add=XOR, mul=AND, sub=XOR, div=DIV) m.SetRow(0, [0, 0, 0, 1, 0, 0, 1, 0]) m.SetRow(1, [1, 1, 1, 0, 1, 0, 1, 1]) m.SetRow(2, [1, 1, 1, 0, 1, 1, 0, 1]) m.SetRow(3, [0, 1, 0, 0, 0, 0, 1, 0]) m.SetRow(4, [0, 1, 1, 1, 1, 1, 1, 0]) m.SetRow(5, [1, 0, 1, 1, 0, 0, 1, 0]) m.SetRow(6, [0, 0, 1, 0, 0, 0, 1, 0]) m.SetRow(7, [0, 0, 0, 0, 0, 1, 0, 0]) print(m) print(m.Inverse())