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- import binascii
- import numpy as np
- from numpy import *
- s_box = (
- 0x63, 0x7C, 0x77, 0x7B, 0xF2, 0x6B, 0x6F, 0xC5, 0x30, 0x01, 0x67, 0x2B, 0xFE, 0xD7, 0xAB, 0x76,
- 0xCA, 0x82, 0xC9, 0x7D, 0xFA, 0x59, 0x47, 0xF0, 0xAD, 0xD4, 0xA2, 0xAF, 0x9C, 0xA4, 0x72, 0xC0,
- 0xB7, 0xFD, 0x93, 0x26, 0x36, 0x3F, 0xF7, 0xCC, 0x34, 0xA5, 0xE5, 0xF1, 0x71, 0xD8, 0x31, 0x15,
- 0x04, 0xC7, 0x23, 0xC3, 0x18, 0x96, 0x05, 0x9A, 0x07, 0x12, 0x80, 0xE2, 0xEB, 0x27, 0xB2, 0x75,
- 0x09, 0x83, 0x2C, 0x1A, 0x1B, 0x6E, 0x5A, 0xA0, 0x52, 0x3B, 0xD6, 0xB3, 0x29, 0xE3, 0x2F, 0x84,
- 0x53, 0xD1, 0x00, 0xED, 0x20, 0xFC, 0xB1, 0x5B, 0x6A, 0xCB, 0xBE, 0x39, 0x4A, 0x4C, 0x58, 0xCF,
- 0xD0, 0xEF, 0xAA, 0xFB, 0x43, 0x4D, 0x33, 0x85, 0x45, 0xF9, 0x02, 0x7F, 0x50, 0x3C, 0x9F, 0xA8,
- 0x51, 0xA3, 0x40, 0x8F, 0x92, 0x9D, 0x38, 0xF5, 0xBC, 0xB6, 0xDA, 0x21, 0x10, 0xFF, 0xF3, 0xD2,
- 0xCD, 0x0C, 0x13, 0xEC, 0x5F, 0x97, 0x44, 0x17, 0xC4, 0xA7, 0x7E, 0x3D, 0x64, 0x5D, 0x19, 0x73,
- 0x60, 0x81, 0x4F, 0xDC, 0x22, 0x2A, 0x90, 0x88, 0x46, 0xEE, 0xB8, 0x14, 0xDE, 0x5E, 0x0B, 0xDB,
- 0xE0, 0x32, 0x3A, 0x0A, 0x49, 0x06, 0x24, 0x5C, 0xC2, 0xD3, 0xAC, 0x62, 0x91, 0x95, 0xE4, 0x79,
- 0xE7, 0xC8, 0x37, 0x6D, 0x8D, 0xD5, 0x4E, 0xA9, 0x6C, 0x56, 0xF4, 0xEA, 0x65, 0x7A, 0xAE, 0x08,
- 0xBA, 0x78, 0x25, 0x2E, 0x1C, 0xA6, 0xB4, 0xC6, 0xE8, 0xDD, 0x74, 0x1F, 0x4B, 0xBD, 0x8B, 0x8A,
- 0x70, 0x3E, 0xB5, 0x66, 0x48, 0x03, 0xF6, 0x0E, 0x61, 0x35, 0x57, 0xB9, 0x86, 0xC1, 0x1D, 0x9E,
- 0xE1, 0xF8, 0x98, 0x11, 0x69, 0xD9, 0x8E, 0x94, 0x9B, 0x1E, 0x87, 0xE9, 0xCE, 0x55, 0x28, 0xDF,
- 0x8C, 0xA1, 0x89, 0x0D, 0xBF, 0xE6, 0x42, 0x68, 0x41, 0x99, 0x2D, 0x0F, 0xB0, 0x54, 0xBB, 0x16
- )
- def place_ct_into_state(ct):
- state_matrix = np.zeros((4, 4), dtype=int)
- for i in range(0, 4):
- state_matrix[i][0] = ct[i + 0]
- for i in range(0, 4):
- state_matrix[i][1] = ct[i + 4]
- for i in range(0, 4):
- state_matrix[i][2] = ct[i + 8]
- for i in range(0, 4):
- state_matrix[i][3] = ct[i + 12]
- return state_matrix
- def add_round_key(state_matrix, round_key):
- for i in range(0, 4):
- state_matrix[i][0] ^= round_key[i + 0]
- for i in range(0, 4):
- state_matrix[i][1] ^= round_key[i + 4]
- for i in range(0, 4):
- state_matrix[i][2] ^= round_key[i + 8]
- for i in range(0, 4):
- state_matrix[i][3] ^= round_key[i + 12]
- def shift_rows(state_matrix):
- state_matrix[1] = np.roll(state_matrix[1], -1)
- state_matrix[2] = np.roll(state_matrix[2], -2)
- state_matrix[3] = np.roll(state_matrix[3], -3)
- def galois_multiplication(a, b):
- p = 0
- hiBitSet = 0
- for i in range(8):
- if b & 1 == 1:
- p ^= a
- hiBitSet = a & 0x80
- a <<= 1
- if hiBitSet == 0x80:
- a ^= 0x1b
- b >>= 1
- return p % 256
- def mix_columns(state_matrix):
- result = []
- for i in range(0, 4):
- result.append(([galois_multiplication(2, state_matrix[:, i][0]) ^ galois_multiplication(3, state_matrix[:, i][
- 1]) ^ galois_multiplication(1, state_matrix[:, i][2]) ^ galois_multiplication(1, state_matrix[:, i][3]),
- galois_multiplication(1, state_matrix[:, i][0]) ^ galois_multiplication(2, state_matrix[:, i][
- 1]) ^ galois_multiplication(3, state_matrix[:, i][2]) ^ galois_multiplication(1,
- state_matrix[
- :, i][
- 3]),
- galois_multiplication(1, state_matrix[:, i][0]) ^ galois_multiplication(1, state_matrix[:, i][
- 1]) ^ galois_multiplication(2, state_matrix[:, i][2]) ^ galois_multiplication(3,
- state_matrix[
- :, i][
- 3]),
- galois_multiplication(3, state_matrix[:, i][0]) ^ galois_multiplication(1, state_matrix[:, i][
- 1]) ^ galois_multiplication(1, state_matrix[:, i][2]) ^ galois_multiplication(2,
- state_matrix[
- :, i][
- 3])
- ]))
- return np.asarray(result).transpose()
- def sub_bytes(state_matrix):
- for i in range(0, 4):
- state_matrix[i][0] = s_box[state_matrix[i][0]]
- for i in range(0, 4):
- state_matrix[i][1] = s_box[state_matrix[i][1]]
- for i in range(0, 4):
- state_matrix[i][2] = s_box[state_matrix[i][2]]
- for i in range(0, 4):
- state_matrix[i][3] = s_box[state_matrix[i][3]]
- def hemming_weight(state_matrix):
- hemming_sum = 0
- for row in np.asarray(state_matrix):
- for value in row:
- hemming_sum += bin(value).count('1')
- return hemming_sum
- plain_texts = []
- with open("pt_low_noise.csv") as infile:
- for line in infile:
- line = binascii.a2b_hex(line.strip('\n'))
- if len(line) != 16:
- print(line)
- plain_texts.append(line)
- for keyGuess in range(0, 255):
- hammingPower = np.zeros(100,10)
- for i in range(0, 100):
- state = place_ct_into_state(plain_texts[i])
- key = [0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, keyGuess]
- for j in range (0,10):
- if len(plain_texts[i]) != 16:
- print(i)
- add_round_key(state, key)
- sub_bytes(state)
- hammingPower[i][j] = state
- shift_rows(state)
- state = mix_columns(state)
- for actualPower in range(0,100):
- for dataPoint in range(0,10):
- scipy.stats.pearsonr(traces,hammingPower[])
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