diff --git a/NIST/SECURE_LCB_FILE_GENERATION.ipynb b/NIST/SECURE_LCB_FILE_GENERATION.ipynb
new file mode 100644
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+++ b/NIST/SECURE_LCB_FILE_GENERATION.ipynb
@@ -0,0 +1,568 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 51,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#1#Header\n",
+ "import csv\n",
+ "import numpy as np\n",
+ "import os \n",
+ "from os import urandom\n",
+ "from keras.models import model_from_json"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 94,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#2#Defining Global Variables\n",
+ "num_rounds = 20\n",
+ "m = 0\n",
+ "o = 0\n",
+ "counter = 0\n",
+ "k_int = 0\n",
+ "k_int1 = 0"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 95,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#3#Defining WORDSIZE\n",
+ "def WORD_SIZE():\n",
+ " return(16);"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 96,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#4#Defining S-Box\n",
+ "s_box_mapping_np = np.array([12, 5, 6, 11, 9, 0, 10, 13, 3, 14, 15, 8, 4, 7, 1, 2], dtype=np.uint8)\n",
+ "\n",
+ "def s_box(input_bits):\n",
+ " input_bits_int = int(input_bits)\n",
+ " output_bits_int = s_box_mapping_np[input_bits_int]\n",
+ " return output_bits_int"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 97,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#5#Defining P-Box\n",
+ "def decimal_to_binary_list(value, num_bits=4):\n",
+ " return np.array([int(x) for x in format(value, f'0{num_bits}b')], dtype=np.uint8)\n",
+ "\n",
+ "def p_box(c_decimal, d_decimal, x_decimal, y_decimal):\n",
+ " c = decimal_to_binary_list(c_decimal)\n",
+ " d = decimal_to_binary_list(d_decimal)\n",
+ " x = decimal_to_binary_list(x_decimal)\n",
+ " y = decimal_to_binary_list(y_decimal)\n",
+ " \n",
+ " e = np.zeros(16, dtype=np.uint8)\n",
+ "\n",
+ " e[0] = d[3]\n",
+ " e[1] = y[1]\n",
+ " e[2] = c[1]\n",
+ " e[3] = x[0]\n",
+ " e[4] = x[3]\n",
+ " e[5] = y[2]\n",
+ " e[6] = c[2]\n",
+ " e[7] = d[1]\n",
+ " e[8] = d[0]\n",
+ " e[9] = x[2]\n",
+ " e[10] = y[3]\n",
+ " e[11] = c[0]\n",
+ " e[12] = c[3]\n",
+ " e[13] = d[2]\n",
+ " e[14] = x[1]\n",
+ " e[15] = y[0]\n",
+ "\n",
+ " return e"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 98,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#6#Defining L-Box\n",
+ "def l_box(f):\n",
+ "\n",
+ " h = np.zeros(16, dtype=np.uint8)\n",
+ " h[0] = f[0]\n",
+ " h[1] = f[8]\n",
+ " h[2] = f[7]\n",
+ " h[3] = f[15]\n",
+ " h[4] = f[1]\n",
+ " h[5] = f[9]\n",
+ " h[6] = f[6]\n",
+ " h[7] = f[14]\n",
+ " h[8] = f[2]\n",
+ " h[9] = f[10]\n",
+ " h[10] = f[5]\n",
+ " h[11] = f[13]\n",
+ " h[12] = f[3]\n",
+ " h[13] = f[11]\n",
+ " h[14] = f[4]\n",
+ " h[15] = f[12]\n",
+ " #print(\"H:\", h)\n",
+ " return h"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 99,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#7#Defining F-function for Right Side of Plaintext\n",
+ "def binary_array_to_integer(output):\n",
+ " int_output = ''.join(map(str, output))\n",
+ " return int(int_output, 2)\n",
+ "\n",
+ "def to_binary(value, bits):\n",
+ " return format(value, f'0{bits}b')\n",
+ "\n",
+ "def f_function(x, key, d):\n",
+ " q=0\n",
+ " global m, counter, k_int\n",
+ " #print(\"X:\", x)\n",
+ " if isinstance(x, int):\n",
+ " x = [x]\n",
+ " input_parts = np.zeros((len(x), 4), dtype=np.uint16)\n",
+ " for i, val in enumerate(x):\n",
+ " input_parts[i] = np.array([val >> 12, (val >> 8) & 0xF, (val >> 4) & 0xF, val & 0xF])\n",
+ " #print(\"F_FUNCTION\")\n",
+ " #print(input_parts)\n",
+ " s_box_outputs = np.array([[s_box(element) for element in part] for part in input_parts])\n",
+ " #print(\"S-box:\", s_box_outputs)\n",
+ " p_box_outputs = np.zeros((len(x), 1, 16), dtype=np.uint8)\n",
+ " for i in range(len(x)):\n",
+ " p_box_outputs[i] = np.array(p_box(s_box_outputs[i][0], s_box_outputs[i][1], s_box_outputs[i][2], s_box_outputs[i][3]))\n",
+ " #print(\"P-box:\", p_box_outputs)\n",
+ " final_outputs = np.zeros(len(x), dtype=np.uint32)\n",
+ " #print(len(x))\n",
+ " for i in range(len(x)):\n",
+ " #print(len(x))\n",
+ " final_output = np.array(l_box(p_box_outputs[i][0]))\n",
+ " k = key[q][(m+1) % 4]\n",
+ " #print(\"final_output:\", final_output)\n",
+ " #print(\"Key:\", k)\n",
+ " if (counter > 1):\n",
+ " #print(\"counter:\", counter)\n",
+ " k_bin, k_int = subsequent_key(k_int)\n",
+ " #print(\"Key in binary:\", k_bin)\n",
+ " #print(\"k in int\", k_int)\n",
+ " output = final_output ^ k_bin\n",
+ " else:\n",
+ " k = to_binary(k,16)\n",
+ " k = np.array([int(bit) for bit in k])\n",
+ " #print(\"k\", k)\n",
+ " output = final_output ^ k\n",
+ " #print(\"XORING output:\", output)\n",
+ " output = binary_array_to_integer(output)\n",
+ " final_outputs[i] = output\n",
+ " q +=1 \n",
+ " #print(\"Final output:\", final_outputs)\n",
+ " if (m < 2):\n",
+ " m +=2\n",
+ " else:\n",
+ " m = 0\n",
+ " \n",
+ " #print(\"_______________________________________________________________\")\n",
+ " return final_outputs"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 100,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#8#Key Generation Algorithm\n",
+ "def to_binary(value, bits):\n",
+ " return format(value, f'0{bits}b')\n",
+ "\n",
+ "def binary_array_to_integer(output):\n",
+ " int_output = ''.join(map(str, output))\n",
+ " return int(int_output, 2)\n",
+ "\n",
+ "def subsequent_key(x):\n",
+ " #x = [x]\n",
+ " if isinstance(x, int):\n",
+ " x = [x]\n",
+ " #print(\"sub key\", x)\n",
+ " input_parts = np.zeros((len(x), 4), dtype=np.uint16)\n",
+ " for i, val in enumerate(x):\n",
+ " input_parts[i] = np.array([val >> 12, (val >> 8) & 0xF, (val >> 4) & 0xF, val & 0xF])\n",
+ " #print(\"input_part\", input_parts)\n",
+ " s_box_outputs = np.array([[s_box(element) for element in part] for part in input_parts])\n",
+ " #print(\"S-box:\", s_box_outputs)\n",
+ " p_box_outputs = np.zeros((len(x), 1, 16), dtype=np.uint8)\n",
+ " for i in range(len(x)):\n",
+ " p_box_outputs[i] = np.array(p_box(s_box_outputs[i][0], s_box_outputs[i][1], s_box_outputs[i][2], s_box_outputs[i][3]))\n",
+ " #print(\"P-box:\", p_box_outputs)\n",
+ " bin_output = np.zeros(len(x), dtype=np.uint16)\n",
+ " final_output = np.zeros(len(x), dtype=np.uint16)\n",
+ " for i in range(len(x)):\n",
+ " bin_output = np.array(l_box(p_box_outputs[i][0]))\n",
+ " #print(bin_output)\n",
+ " #final_outputs[i] = final_output\n",
+ " output = binary_array_to_integer(bin_output)\n",
+ " #print(output)\n",
+ " final_output[i] = output\n",
+ " \n",
+ " #print(\"final_outputs:\", final_outputs)\n",
+ " return bin_output, final_output"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 101,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#9#Defining F-function for Left Side of Plaintext\n",
+ "def binary_array_to_integer(output):\n",
+ " int_output = ''.join(map(str, output))\n",
+ " return int(int_output, 2)\n",
+ "\n",
+ "def ff_function(x, key, d):\n",
+ " q=0\n",
+ " global o, counter, k_int1\n",
+ " if isinstance(x, int):\n",
+ " x = [x]\n",
+ " \n",
+ " input_parts = np.zeros((len(x), 4), dtype=np.uint16)\n",
+ " for i, val in enumerate(x):\n",
+ " input_parts[i] = np.array([val >> 12, (val >> 8) & 0xF, (val >> 4) & 0xF, val & 0xF])\n",
+ " #print(\"FF_FUNCTION\")\n",
+ " #print(input_parts)\n",
+ " s_box_outputs = np.array([[s_box(element) for element in part] for part in input_parts])\n",
+ " #print(\"S-box:\", s_box_outputs)\n",
+ " p_box_outputs = np.zeros((len(x), 1, 16), dtype=np.uint8)\n",
+ " for i in range(len(x)):\n",
+ " p_box_outputs[i] = np.array(p_box(s_box_outputs[i][0], s_box_outputs[i][1], s_box_outputs[i][2], s_box_outputs[i][3]))\n",
+ " #print(\"P-box:\", p_box_outputs)\n",
+ " final_outputs = np.zeros(len(x), dtype=np.uint32)\n",
+ " #print(len(x))\n",
+ " for i in range(len(x)):\n",
+ " #print(len(x))\n",
+ " final_output = np.array(l_box(p_box_outputs[i][0]))\n",
+ " k = key[q][o % 4]\n",
+ " #print(\"final_output:\", final_output)\n",
+ " #print(\"Key in int:\", k)\n",
+ " if (counter > 1):\n",
+ " k_bin, k_int1 = subsequent_key(k_int1)\n",
+ " #print(\"Key in binary:\", k_bin)\n",
+ " #print(\"k\", k_int)\n",
+ " output = final_output ^ k_bin\n",
+ " else:\n",
+ " k = to_binary(k,16)\n",
+ " k = np.array([int(bit) for bit in k])\n",
+ " #print(\"k\", k)\n",
+ " output = final_output ^ k\n",
+ " #print(\"XORING output:\", output)\n",
+ " output = binary_array_to_integer(output)\n",
+ " final_outputs[i] = output\n",
+ " q +=1 \n",
+ " counter += 1\n",
+ " #print(\"Final output:\", final_outputs)\n",
+ " if (o < 2):\n",
+ " o +=2\n",
+ " else:\n",
+ " o = 0\n",
+ " #print(\"_______________________________________________________________\")\n",
+ " return final_outputs"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 116,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#9#Convert the ciphertext pairs into Binary array\n",
+ "def convert_to_binary(row):\n",
+ " bin_array = np.zeros(32, dtype=np.uint8)\n",
+ " binary_str = format(row[0], '016b') + format(row[1], '016b')\n",
+ " for i, b in enumerate(binary_str):\n",
+ " bin_array[i] = int(b)\n",
+ " return bin_array"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 103,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#10#Encryption Function\n",
+ "def lcb_encrypt(plaintext, key, rounds, d):\n",
+ " \n",
+ " left_plaintext = np.uint16(plaintext[0])\n",
+ " right_plaintext = np.uint16(plaintext[1])\n",
+ " L, R = left_plaintext, right_plaintext\n",
+ "\n",
+ " n = 0\n",
+ " \n",
+ " while n < rounds:\n",
+ " L, R = f_function(R, key, d), ff_function(L, key, d)\n",
+ " n += 1\n",
+ " print(\"Encryption done per round\") \n",
+ " #print(rounds)\n",
+ " #print(n)\n",
+ " return (L, R)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 104,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#11#Function for generation of keys\n",
+ "import random\n",
+ "\n",
+ "def generate_hex_keys(num_keys, length=16):\n",
+ " hex_chars = \"0123456789ABCDEF\"\n",
+ " keys_str = [\"\".join(random.choices(hex_chars, k=length)) for _ in range(num_keys)]\n",
+ "\n",
+ " return keys_str\n",
+ "\n",
+ "def generate_round_keys(num_keys):\n",
+ " random_keys_hex = generate_hex_keys(num_keys)\n",
+ " #random_keys_hex = ['D63A529ECC92D353', '563A529ECC92D353', '163A529ECC92D353', 'D67AD296CC92DB53', '76BA569EDC9BD353']\n",
+ " #random_keys_hex = ['163A529D687529EC']\n",
+ " round_keys = []\n",
+ " \n",
+ " for random_key_hex in random_keys_hex:\n",
+ " random_key = int(random_key_hex, 16)\n",
+ "\n",
+ " K1 = (random_key >> 48) & 0xFFFF\n",
+ " K2 = (random_key >> 32) & 0xFFFF\n",
+ " K3 = (random_key >> 16) & 0xFFFF\n",
+ " K4 = random_key & 0xFFFF\n",
+ " \n",
+ " #k1_bin = to_binary(K1, 16)\n",
+ " #k2_bin = to_binary(K2, 16)\n",
+ " #k3_bin = to_binary(K3, 16)\n",
+ " #k4_bin = to_binary(K4, 16)\n",
+ "\n",
+ " #k1_np_array = np.array([int(bit) for bit in k1_bin])\n",
+ " #k2_np_array = np.array([int(bit) for bit in k2_bin])\n",
+ " #k3_np_array = np.array([int(bit) for bit in k3_bin])\n",
+ " #k4_np_array = np.array([int(bit) for bit in k4_bin])\n",
+ "\n",
+ " round_key = np.array([K1, K2, K3, K4])\n",
+ " round_keys.append(round_key)\n",
+ " round_key = np.array(round_keys)\n",
+ " #print(\"Key generation done:\", round_keys)\n",
+ " return round_key"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 133,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "#12#Make dataset\n",
+ "\n",
+ "def make_train_data(n, nr, var):\n",
+ " global counter\n",
+ "\n",
+ " nonce = np.frombuffer(urandom(2), dtype=np.uint16);\n",
+ " cownter = np.arange(0,1023, dtype=np.uint16)\n",
+ " input = (nonce.astype(np.uint32) << 16) | cownter.astype(np.uint32)\n",
+ " plaintext = np.frombuffer(urandom(4*n), dtype=np.uint32);\n",
+ " #plaintext = [0xEED4B555]\n",
+ " #plaintext = [0xCED4B5C6, 0xCED4B5C6, 0xCED4B5C6, 0xCED4B5C6, 0xCED4B5C6]\n",
+ " plain0l = np.empty(n, dtype=np.uint16)\n",
+ " plain0r = np.empty(n, dtype=np.uint16)\n",
+ " plaintext0l = np.frombuffer(urandom(2*n), dtype=np.uint16)\n",
+ " plaintext0r = np.frombuffer(urandom(2*n), dtype=np.uint16)\n",
+ " \n",
+ " for i in range(n):\n",
+ " plain0l[i] = (input[i] >> 16) & 0xffff\n",
+ " plain0r[i] = input[i] & 0xffff\n",
+ " \n",
+ " round_keys = generate_round_keys(1)\n",
+ " \n",
+ " round_key = np.repeat(round_keys, 1024, axis=0)\n",
+ " \n",
+ " ctdata0l, ctdata0r = lcb_encrypt((plain0l, plain0r), round_key, nr, n)\n",
+ " ciphertext0l = ctdata0l ^ plaintext0l\n",
+ " print(ciphertext0l[0])\n",
+ " ciphertext0r = ctdata0r ^ plaintext0r\n",
+ " print(ciphertext0r[0])\n",
+ " ctdata = np.vstack((ciphertext0l, ciphertext0r)).T\n",
+ " \n",
+ " X = np.array([convert_to_binary(row) for row in ctdata])\n",
+ " print(X[0])\n",
+ " X = X.reshape(1, -1)\n",
+ " \n",
+ " filename = f\"output_{var}.txt\"\n",
+ "\n",
+ "# Open the file in write mode (overwrites existing file or creates a new one)\n",
+ " with open(filename, 'w') as file:\n",
+ " # Convert the array to a string without spaces\n",
+ " X_string = ''.join(X.astype(str)[0])\n",
+ "\n",
+ " # Write the string to the file\n",
+ " file.write(X_string)\n",
+ " \n",
+ " \"\"\"\n",
+ " with open(\"Dataset_NewP.csv\", \"w\", newline='') as f:\n",
+ " writer = csv.writer(f)\n",
+ " writer.writerow([\"plain0l\", \"plain0r\", \"plain1l\", \"plain1r\",\"Y\"])\n",
+ " for i in range(n):\n",
+ " writer.writerow([plain0l[i], plain0r[i], plain1l[i], plain1r[i],Y[i]])\n",
+ "\n",
+ " with open(\"Dataset_NewC.csv\", \"w\", newline='') as f:\n",
+ " writer = csv.writer(f)\n",
+ " writer.writerow([\"ctdata0l\", \"ctdata0r\", \"ctdata1l\", \"ctdata1r\",\"Y\"])\n",
+ " for i in range(n):\n",
+ " writer.writerow([ctdata0l[i], ctdata0r[i], ctdata1l[i], ctdata1r[i],Y[i]])\n",
+ " \"\"\"\n",
+ " return(X);"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 134,
+ "metadata": {
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Encryption done per round\n",
+ "25812\n",
+ "59196\n",
+ "[0 1 1 0 0 1 0 0 1 1 0 1 0 1 0 0 1 1 1 0 0 1 1 1 0 0 1 1 1 1 0 0]\n",
+ "Encryption done per round\n",
+ "65099\n",
+ "11722\n",
+ "[1 1 1 1 1 1 1 0 0 1 0 0 1 0 1 1 0 0 1 0 1 1 0 1 1 1 0 0 1 0 1 0]\n",
+ "Encryption done per round\n",
+ "35646\n",
+ "42735\n",
+ "[1 0 0 0 1 0 1 1 0 0 1 1 1 1 1 0 1 0 1 0 0 1 1 0 1 1 1 0 1 1 1 1]\n",
+ "Encryption done per round\n",
+ "1385\n",
+ "17212\n",
+ "[0 0 0 0 0 1 0 1 0 1 1 0 1 0 0 1 0 1 0 0 0 0 1 1 0 0 1 1 1 1 0 0]\n",
+ "Encryption done per round\n",
+ "53116\n",
+ "9840\n",
+ "[1 1 0 0 1 1 1 1 0 1 1 1 1 1 0 0 0 0 1 0 0 1 1 0 0 1 1 1 0 0 0 0]\n",
+ "Encryption done per round\n",
+ "46666\n",
+ "41535\n",
+ "[1 0 1 1 0 1 1 0 0 1 0 0 1 0 1 0 1 0 1 0 0 0 1 0 0 0 1 1 1 1 1 1]\n",
+ "Encryption done per round\n",
+ "56968\n",
+ "29415\n",
+ "[1 1 0 1 1 1 1 0 1 0 0 0 1 0 0 0 0 1 1 1 0 0 1 0 1 1 1 0 0 1 1 1]\n",
+ "Encryption done per round\n",
+ "19138\n",
+ "32283\n",
+ "[0 1 0 0 1 0 1 0 1 1 0 0 0 0 1 0 0 1 1 1 1 1 1 0 0 0 0 1 1 0 1 1]\n",
+ "Encryption done per round\n",
+ "29708\n",
+ "61356\n",
+ "[0 1 1 1 0 1 0 0 0 0 0 0 1 1 0 0 1 1 1 0 1 1 1 1 1 0 1 0 1 1 0 0]\n",
+ "Encryption done per round\n",
+ "60847\n",
+ "3956\n",
+ "[1 1 1 0 1 1 0 1 1 0 1 0 1 1 1 1 0 0 0 0 1 1 1 1 0 1 1 1 0 1 0 0]\n"
+ ]
+ }
+ ],
+ "source": [
+ "for i in range (1000000):\n",
+ " make_train_data(1023,20,i)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 136,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Define the number of files and bits per row\n",
+ "num_files = 1000000\n",
+ "bits_per_row = 32736\n",
+ "\n",
+ "# Initialize the merged array\n",
+ "merged_array = []\n",
+ "\n",
+ "# Iterate over the files and read the content\n",
+ "for i in range(num_files):\n",
+ " file_name = f\"output_{i}.txt\" # Adjust the file name pattern if needed\n",
+ " i +=1\n",
+ " with open(file_name, 'r') as file:\n",
+ " content = file.read()\n",
+ " merged_array.append(content)\n",
+ "\n",
+ "# Convert the merged array into a single string with newline characters\n",
+ "merged_string = '\\n'.join(merged_array)\n",
+ "\n",
+ "# Write the merged string to the output file\n",
+ "output_file = \"merged_output.txt\"\n",
+ "with open(output_file, 'w') as file:\n",
+ " file.write(merged_string)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
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