import numpy as np
from numpy import genfromtxt
import pandas as pd
import csv
import matplotlib.pyplot as plt
inputfile = 0
plt.style.use("seaborn-darkgrid")
font = {'size'   : 15}
plt.rc('font', **font)

Sbox = [
            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 onecount(inputval):
    temp = bin(inputval).count('1')
    return int(temp)

my_data = np.array(genfromtxt('inputs0.dat', delimiter=',',dtype=int))
traceData = np.array(genfromtxt('T0.dat', delimiter=',',dtype=float))
print("traceData - Columns: "+str(len(traceData)))
print("traceData - Rows: "+str(len(traceData[0])))

HW = np.zeros(shape=(600,256),dtype=int)
for inputindex, inputdata in enumerate(my_data):
    for keyvalue in range(256): #0 to 255 (all key values)
        HW[inputindex,keyvalue] = onecount(Sbox[inputdata ^ keyvalue])

print("HW - Columns: "+str(len(HW)))
print("HW - Rows: "+str(len(HW[0])))


x = np.arange(1,10,1).reshape(-1,1)
dataframe = pd.DataFrame.from_records(x)

HWpd = pd.DataFrame.from_records(HW)
traceDatapd = pd.DataFrame.from_records(traceData)

correlationArray = []
for correlationIndex in range(256):
    temp = 0
    correlation = 0
    for traceIndex in range(55):
        if (temp > correlation):
            correlation = temp
        temp = HWpd[correlationIndex].corr(traceDatapd[traceIndex])
    correlationArray.append(correlation)

print("CorrelationArray Length: "+str(len(correlationArray)))
print(correlationArray)
print(len(correlationArray))
print(np.sort(correlationArray))
print(np.max(correlationArray))
keybyteval = np.argmax(correlationArray)
print("Secret Key Byte Value: " + str(keybyteval))

extraticks = [keybyteval]
fig1, ax1 = plt.subplots(1,figsize=(12,9))
ax1.scatter(range(0,256),correlationArray,marker='o',s=25,alpha=0.6)
ax1.plot(keybyteval,np.max(correlationArray),'or')
ax1.axvline(x=keybyteval,ymax=0.94,color='red', linestyle=':')
ax1.set_ylabel('Correlation Coefficent')
ax1.set_xlabel('Key Byte Value')
plt.xticks(list(plt.xticks()[0]) + extraticks)
plt.show()