--- /dev/null
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "import matplotlib.pyplot as plt\n",
+ "import pandas as pd\n",
+ "import collections\n",
+ "import string\n",
+ "import numpy as np\n",
+ "from numpy import matrix\n",
+ "from numpy import linalg\n",
+ "%matplotlib inline\n",
+ "\n",
+ "from multiprocessing import Pool\n",
+ "\n",
+ "\n",
+ "from cipher import *\n",
+ "from cipherbreak import *\n",
+ "\n",
+ "c7b = open('2016/7b.ciphertext').read()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 108,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "c7bs = sanitise(c7b)\n",
+ "c7br = cat(reversed(c7bs))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "def bifid_grid(keyword, wrap_alphabet, letter_mapping):\n",
+ " cipher_alphabet = keyword_cipher_alphabet_of(keyword, wrap_alphabet)\n",
+ " if letter_mapping is None:\n",
+ " letter_mapping = {'j': 'i'}\n",
+ " translation = ''.maketrans(letter_mapping)\n",
+ " cipher_alphabet = cat(collections.OrderedDict.fromkeys(cipher_alphabet.translate(translation)))\n",
+ " f_grid = {k: ((i // 5) + 1, (i % 5) + 1) \n",
+ " for i, k in enumerate(cipher_alphabet)}\n",
+ " r_grid = {((i // 5) + 1, (i % 5) + 1): k \n",
+ " for i, k in enumerate(cipher_alphabet)}\n",
+ " return translation, f_grid, r_grid"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 156,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "import pprint"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 157,
+ "metadata": {
+ "collapsed": false,
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "({106: 'i'},\n",
+ " {'a': (1, 4),\n",
+ " 'b': (2, 1),\n",
+ " 'c': (2, 2),\n",
+ " 'd': (2, 3),\n",
+ " 'e': (2, 4),\n",
+ " 'f': (2, 5),\n",
+ " 'g': (1, 2),\n",
+ " 'h': (3, 1),\n",
+ " 'i': (1, 1),\n",
+ " 'k': (3, 2),\n",
+ " 'l': (3, 3),\n",
+ " 'm': (3, 4),\n",
+ " 'n': (1, 5),\n",
+ " 'o': (3, 5),\n",
+ " 'p': (4, 1),\n",
+ " 'q': (4, 2),\n",
+ " 'r': (4, 3),\n",
+ " 's': (4, 4),\n",
+ " 't': (4, 5),\n",
+ " 'u': (1, 3),\n",
+ " 'v': (5, 1),\n",
+ " 'w': (5, 2),\n",
+ " 'x': (5, 3),\n",
+ " 'y': (5, 4),\n",
+ " 'z': (5, 5)},\n",
+ " {(1, 1): 'i',\n",
+ " (1, 2): 'g',\n",
+ " (1, 3): 'u',\n",
+ " (1, 4): 'a',\n",
+ " (1, 5): 'n',\n",
+ " (2, 1): 'b',\n",
+ " (2, 2): 'c',\n",
+ " (2, 3): 'd',\n",
+ " (2, 4): 'e',\n",
+ " (2, 5): 'f',\n",
+ " (3, 1): 'h',\n",
+ " (3, 2): 'k',\n",
+ " (3, 3): 'l',\n",
+ " (3, 4): 'm',\n",
+ " (3, 5): 'o',\n",
+ " (4, 1): 'p',\n",
+ " (4, 2): 'q',\n",
+ " (4, 3): 'r',\n",
+ " (4, 4): 's',\n",
+ " (4, 5): 't',\n",
+ " (5, 1): 'v',\n",
+ " (5, 2): 'w',\n",
+ " (5, 3): 'x',\n",
+ " (5, 4): 'y',\n",
+ " (5, 5): 'z'})\n"
+ ]
+ }
+ ],
+ "source": [
+ "pprint.pprint(bifid_grid('iguana', KeywordWrapAlphabet.from_a, None))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 158,
+ "metadata": {
+ "collapsed": false,
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "({106: 'i'},\n",
+ " {'a': (1, 2),\n",
+ " 'b': (1, 3),\n",
+ " 'c': (1, 4),\n",
+ " 'd': (1, 5),\n",
+ " 'e': (2, 1),\n",
+ " 'f': (2, 2),\n",
+ " 'g': (2, 3),\n",
+ " 'h': (2, 4),\n",
+ " 'i': (2, 5),\n",
+ " 'k': (3, 1),\n",
+ " 'l': (3, 2),\n",
+ " 'm': (3, 3),\n",
+ " 'n': (3, 4),\n",
+ " 'o': (3, 5),\n",
+ " 'p': (4, 1),\n",
+ " 'q': (4, 2),\n",
+ " 'r': (4, 3),\n",
+ " 's': (4, 4),\n",
+ " 't': (4, 5),\n",
+ " 'u': (5, 1),\n",
+ " 'v': (5, 2),\n",
+ " 'w': (5, 3),\n",
+ " 'x': (5, 4),\n",
+ " 'y': (5, 5),\n",
+ " 'z': (1, 1)},\n",
+ " {(1, 1): 'z',\n",
+ " (1, 2): 'a',\n",
+ " (1, 3): 'b',\n",
+ " (1, 4): 'c',\n",
+ " (1, 5): 'd',\n",
+ " (2, 1): 'e',\n",
+ " (2, 2): 'f',\n",
+ " (2, 3): 'g',\n",
+ " (2, 4): 'h',\n",
+ " (2, 5): 'i',\n",
+ " (3, 1): 'k',\n",
+ " (3, 2): 'l',\n",
+ " (3, 3): 'm',\n",
+ " (3, 4): 'n',\n",
+ " (3, 5): 'o',\n",
+ " (4, 1): 'p',\n",
+ " (4, 2): 'q',\n",
+ " (4, 3): 'r',\n",
+ " (4, 4): 's',\n",
+ " (4, 5): 't',\n",
+ " (5, 1): 'u',\n",
+ " (5, 2): 'v',\n",
+ " (5, 3): 'w',\n",
+ " (5, 4): 'x',\n",
+ " (5, 5): 'y'})\n"
+ ]
+ }
+ ],
+ "source": [
+ "pprint.pprint(bifid_grid('z', KeywordWrapAlphabet.from_a, None))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 159,
+ "metadata": {
+ "collapsed": false,
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "({113: 'p'},\n",
+ " {'a': (1, 4),\n",
+ " 'b': (2, 1),\n",
+ " 'c': (2, 2),\n",
+ " 'd': (2, 3),\n",
+ " 'e': (2, 4),\n",
+ " 'f': (2, 5),\n",
+ " 'g': (1, 2),\n",
+ " 'h': (3, 1),\n",
+ " 'i': (1, 1),\n",
+ " 'j': (3, 2),\n",
+ " 'k': (3, 3),\n",
+ " 'l': (3, 4),\n",
+ " 'm': (3, 5),\n",
+ " 'n': (1, 5),\n",
+ " 'o': (4, 1),\n",
+ " 'p': (4, 2),\n",
+ " 'r': (4, 3),\n",
+ " 's': (4, 4),\n",
+ " 't': (4, 5),\n",
+ " 'u': (1, 3),\n",
+ " 'v': (5, 1),\n",
+ " 'w': (5, 2),\n",
+ " 'x': (5, 3),\n",
+ " 'y': (5, 4),\n",
+ " 'z': (5, 5)},\n",
+ " {(1, 1): 'i',\n",
+ " (1, 2): 'g',\n",
+ " (1, 3): 'u',\n",
+ " (1, 4): 'a',\n",
+ " (1, 5): 'n',\n",
+ " (2, 1): 'b',\n",
+ " (2, 2): 'c',\n",
+ " (2, 3): 'd',\n",
+ " (2, 4): 'e',\n",
+ " (2, 5): 'f',\n",
+ " (3, 1): 'h',\n",
+ " (3, 2): 'j',\n",
+ " (3, 3): 'k',\n",
+ " (3, 4): 'l',\n",
+ " (3, 5): 'm',\n",
+ " (4, 1): 'o',\n",
+ " (4, 2): 'p',\n",
+ " (4, 3): 'r',\n",
+ " (4, 4): 's',\n",
+ " (4, 5): 't',\n",
+ " (5, 1): 'v',\n",
+ " (5, 2): 'w',\n",
+ " (5, 3): 'x',\n",
+ " (5, 4): 'y',\n",
+ " (5, 5): 'z'})\n"
+ ]
+ }
+ ],
+ "source": [
+ "pprint.pprint(bifid_grid('iguana', KeywordWrapAlphabet.from_a, {'q': 'p'}))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 87,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# def bifid_decipher(message, keyword, wrap_alphabet=KeywordWrapAlphabet.from_a, \n",
+ "# letter_mapping=None, period=None):\n",
+ "# translation, f_grid, r_grid = bifid_grid(keyword, wrap_alphabet, letter_mapping)\n",
+ " \n",
+ "# t_message = message.translate(translation)\n",
+ "# pairs0 = [f_grid[l] for l in t_message]\n",
+ "# items = sum([list(p) for p in pairs0], [])\n",
+ "# gap = len(message)\n",
+ "# pairs1 = [(items[i//2], items[i//2+gap]) for i in range(0, len(items), 2)]\n",
+ "# return cat(r_grid[p] for p in pairs1)\n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 162,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "def bifid_encipher(message, keyword, wrap_alphabet=KeywordWrapAlphabet.from_a, \n",
+ " letter_mapping=None, period=None, fillvalue=None):\n",
+ " translation, f_grid, r_grid = bifid_grid(keyword, wrap_alphabet, letter_mapping)\n",
+ " \n",
+ " t_message = message.translate(translation)\n",
+ " pairs0 = [f_grid[l] for l in sanitise(t_message)]\n",
+ " if period:\n",
+ " chunked_pairs = [pairs0[i:i+period] for i in range(0, len(pairs0), period)]\n",
+ " if len(chunked_pairs[-1]) < period and fillvalue:\n",
+ " chunked_pairs[-1] += [f_grid[fillvalue]] * (period - len(chunked_pairs[-1]))\n",
+ " else:\n",
+ " chunked_pairs = [pairs0]\n",
+ " \n",
+ " pairs1 = []\n",
+ " for c in chunked_pairs:\n",
+ " items = sum(list(list(i) for i in zip(*c)), [])\n",
+ " p = [(items[i], items[i+1]) for i in range(0, len(items), 2)]\n",
+ " pairs1 += p\n",
+ " \n",
+ " return cat(r_grid[p] for p in pairs1)\n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 163,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'nkklawamdkoedysipdesltirsnoesqlvvaloderbhel'"
+ ]
+ },
+ "execution_count": 163,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "bifid_encipher('this is a test message for the keyword decipherment', 'elephant', wrap_alphabet=KeywordWrapAlphabet.from_last)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 83,
+ "metadata": {
+ "collapsed": false,
+ "scrolled": true
+ },
+ "outputs": [],
+ "source": [
+ "ot, ofg, org = bifid_grid('iguana', KeywordWrapAlphabet.from_a, None)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 85,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[(1, 1),\n",
+ " (1, 5),\n",
+ " (2, 3),\n",
+ " (1, 1),\n",
+ " (1, 4),\n",
+ " (2, 2),\n",
+ " (1, 3),\n",
+ " (4, 3),\n",
+ " (4, 3),\n",
+ " (5, 4)]"
+ ]
+ },
+ "execution_count": 85,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "op0 = [ofg[l] for l in \"indiacurry\"]\n",
+ "op0"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 86,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[[(1, 1), (1, 5), (2, 3), (1, 1)],\n",
+ " [(1, 4), (2, 2), (1, 3), (4, 3)],\n",
+ " [(4, 3), (5, 4), (1, 4), (1, 4)]]"
+ ]
+ },
+ "execution_count": 86,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "ocp = chunks(op0, 4, fillvalue=[[ofg['a']]])\n",
+ "acc = []\n",
+ "ocp"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 87,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[(1, 1),\n",
+ " (2, 1),\n",
+ " (1, 5),\n",
+ " (3, 1),\n",
+ " (1, 2),\n",
+ " (1, 4),\n",
+ " (4, 2),\n",
+ " (3, 3),\n",
+ " (4, 5),\n",
+ " (1, 1),\n",
+ " (3, 4),\n",
+ " (4, 4)]"
+ ]
+ },
+ "execution_count": 87,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "acc=[]\n",
+ "for c in ocp:\n",
+ " items = sum(list(list(i) for i in zip(*c)), [])\n",
+ " p = [(items[i], items[i+1]) for i in range(0, len(items), 2)]\n",
+ " acc += p\n",
+ "acc"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 88,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'ibnhgaqltims'"
+ ]
+ },
+ "execution_count": 88,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "cat(org[p] for p in acc)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 164,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "def bifid_decipher(message, keyword, wrap_alphabet=KeywordWrapAlphabet.from_a, \n",
+ " letter_mapping=None, period=None, fillvalue=None):\n",
+ " translation, f_grid, r_grid = bifid_grid(keyword, wrap_alphabet, letter_mapping)\n",
+ " \n",
+ " t_message = message.translate(translation)\n",
+ " pairs0 = [f_grid[l] for l in sanitise(t_message)]\n",
+ " if period:\n",
+ " chunked_pairs = [pairs0[i:i+period] for i in range(0, len(pairs0), period)]\n",
+ " if len(chunked_pairs[-1]) < period and fillvalue:\n",
+ " chunked_pairs[-1] += [f_grid[fillvalue]] * (period - len(chunked_pairs[-1]))\n",
+ " else:\n",
+ " chunked_pairs = [pairs0]\n",
+ " \n",
+ " pairs1 = []\n",
+ " for c in chunked_pairs:\n",
+ " items = [j for i in c for j in i]\n",
+ " gap = len(c)\n",
+ " p = [(items[i], items[i+gap]) for i in range(gap)]\n",
+ " pairs1 += p\n",
+ "\n",
+ " return cat(r_grid[p] for p in pairs1) "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false,
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "({106: 'i'},\n",
+ " {'a': (1, 4),\n",
+ " 'b': (2, 1),\n",
+ " 'c': (2, 2),\n",
+ " 'd': (2, 3),\n",
+ " 'e': (2, 4),\n",
+ " 'f': (2, 5),\n",
+ " 'g': (1, 2),\n",
+ " 'h': (3, 1),\n",
+ " 'i': (1, 1),\n",
+ " 'k': (3, 2),\n",
+ " 'l': (3, 3),\n",
+ " 'm': (3, 4),\n",
+ " 'n': (1, 5),\n",
+ " 'o': (3, 5),\n",
+ " 'p': (4, 1),\n",
+ " 'q': (4, 2),\n",
+ " 'r': (4, 3),\n",
+ " 's': (4, 4),\n",
+ " 't': (4, 5),\n",
+ " 'u': (1, 3),\n",
+ " 'v': (5, 1),\n",
+ " 'w': (5, 2),\n",
+ " 'x': (5, 3),\n",
+ " 'y': (5, 4),\n",
+ " 'z': (5, 5)},\n",
+ " {(1, 1): 'i',\n",
+ " (1, 2): 'g',\n",
+ " (1, 3): 'u',\n",
+ " (1, 4): 'a',\n",
+ " (1, 5): 'n',\n",
+ " (2, 1): 'b',\n",
+ " (2, 2): 'c',\n",
+ " (2, 3): 'd',\n",
+ " (2, 4): 'e',\n",
+ " (2, 5): 'f',\n",
+ " (3, 1): 'h',\n",
+ " (3, 2): 'k',\n",
+ " (3, 3): 'l',\n",
+ " (3, 4): 'm',\n",
+ " (3, 5): 'o',\n",
+ " (4, 1): 'p',\n",
+ " (4, 2): 'q',\n",
+ " (4, 3): 'r',\n",
+ " (4, 4): 's',\n",
+ " (4, 5): 't',\n",
+ " (5, 1): 'v',\n",
+ " (5, 2): 'w',\n",
+ " (5, 3): 'x',\n",
+ " (5, 4): 'y',\n",
+ " (5, 5): 'z'})"
+ ]
+ },
+ "execution_count": 5,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "bifid_grid('iguana', KeywordWrapAlphabet.from_a, None)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 139,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'ibidonhprm'"
+ ]
+ },
+ "execution_count": 139,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "bifid_encipher(\"indiajelly\", 'iguana')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 140,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'indiaielly'"
+ ]
+ },
+ "execution_count": 140,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "bifid_decipher('ibidonhprm', 'iguana')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 137,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'ibnhgaqltm'"
+ ]
+ },
+ "execution_count": 137,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "bifid_encipher(\"indiacurry\", 'iguana', period=4)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 138,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'indiacurry'"
+ ]
+ },
+ "execution_count": 138,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "bifid_decipher(\"ibnhgaqltm\", 'iguana', period=4)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 144,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'ibnhgaqltzml'"
+ ]
+ },
+ "execution_count": 144,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "bifid_encipher(\"indiacurry\", 'iguana', period=4, fillvalue='x')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 146,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'indiacurryxx'"
+ ]
+ },
+ "execution_count": 146,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "bifid_decipher(\"ibnhgaqltzml\", 'iguana', period=4)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 101,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "p0 = [(1, 1), (2, 1), (1, 5), (3, 1)]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 103,
+ "metadata": {
+ "collapsed": false,
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[1, 1, 2, 1, 1, 5, 3, 1]"
+ ]
+ },
+ "execution_count": 103,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "t0 = [j for i in p0 for j in i]\n",
+ "t0"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 104,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[(1, 1), (1, 5), (2, 3), (1, 1)]"
+ ]
+ },
+ "execution_count": 104,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "[(t0[i], t0[i+4]) for i in range(4)]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 130,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'martinwehavemadeadreadfulmistakeandihavebeentooslowtoadmitthattomyselfihavehadavisitfromthewomanfromthesyndicateandiconfrontedheraboutthesourceofthetemplatessheconfirmedmyworstfearsandnowiwanttocrawlawayanddiewhathavewedoneoursoftwarehasledtosomuchsufferingwhenitwasdesignedtodotheoppositeiaskedherhowthecabinetofficecouldpossiblyhaveauthorisedthisandshelaughedandexplainedthatthesyndicatenolongerworkedforthebritishgovernmentcallitprivateenterpriseshesaidwehavealwaysbeengoodatthatmyhorrormusthavebeenwrittenallovermyfaceshedidntseemsurprisedatmyreactionbutequallyshedidnttakeitwellandcivilitywasabandonediaskedherhowitcouldbelegalletalonemoraltodowhattheyproposedandheranswerwasthatitwasnecessaryisaidwewouldnthelpthemandshesaiditwasnecessarythatwedidisaidiwouldntbeabletofacemyfamilyandfriendsifwecooperatedandshesaidiwouldnthavetoworryaboutthatforlongonewayoranotherthepdssyndicateweregoingtomakesurewebothdisappearedlookingbackicanseethatfromthestartthiswholethinghasactedtodrawusintoitscentreandnowiamattheeventhorizonalmostunabletoescapeitspullbutithinkwehaveonelastchanceiamsureshewillbevisitingyouaswellshethinkswehavenochoicebutithinkachoiceisallwehavewhateveryoudoholdoutforbettertermsshehastobelievethatyouareonsideandmotivatedbygreedsothatshewontworryaboutanyqualmsyoumighthaveconvinceherthatyouwillconvincemetocooperatetellherthatyouthinkyoushouldworkfromthecollectiveinosloandthatyouwantpaymentviathebankinswitzerlandigottheimpressionthatmoneyisnotaproblemwithmoneyinaswissbankandtheexpertiseandconnectivityaffordedbythecollectiveithinkwehaveachancetoescapeandtotrytostopthemperhapswewillsurvivethisperhapswecanbringthemdown'"
+ ]
+ },
+ "execution_count": 130,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "bifid_decipher(c7bs, 'ligo', KeywordWrapAlphabet.from_a, period=4, fillvalue=None)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 147,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'martin we have made a dreadful mistake and i have been too slow to admit that to myself i have had a visit from the woman from the syndicate and i confronted her about the source of the templates she confirmed my worst fears and now i want to crawl away and die what have we done our software has led to so much suffering when it was designed to do the opposite i asked her how the cabinet office could possibly have authorised this and she laughed and explained that the syndicate no longer worked for the british government call it private enterprises he said we have always been good at that my horror must have been written all over myfaces he didnt seem surprised at my reaction but equally she didnt take it well and civility was abandoned i asked her how it could be legal let alone moral to do what they proposed and her answer was that it was necessary i said we wouldnt help them and she said it was necessary that we did i said i wouldnt be able to face my family and friends if we cooperated and she said i wouldnt have to worry about that for long one way or another the pds syndicate were going to make sure we both disappeared looking back i can see that from the start this whole thing has acted to draw us into its centre and now i am at the event horizon almost unable to escape its pull but i think we have one last chance i am sure she will be visiting you as well she thinks we have no choice but i think a choice is all we have whatever you do hold out for better terms she has to believe that you are on side and motivated by greed so that she wont worry about any qualms you might have convince her that you will convince me to cooperate tell her that you think you should work from the collective in oslo and that you want payment via the bank in switzerland i got the impression that money is not a problem with money in a swiss bank and the expertise and connectivity afforded by the collective i think we have a chance to escape and to try to stop them perhaps we will survive this perhaps we can bring them down'"
+ ]
+ },
+ "execution_count": 147,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "wcat(segment(bifid_decipher(c7bs, 'ligo', KeywordWrapAlphabet.from_a, period=4)))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 49,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "p0 = [(2, 1), (3, 3), (3, 3), (5, 1), (1, 4)]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 54,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[2, 1, 3, 3, 3, 3, 5, 1, 1, 4]"
+ ]
+ },
+ "execution_count": 54,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "items = sum([list(p) for p in p0], [])\n",
+ "items"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 55,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[(2, 3), (1, 5), (3, 1), (3, 1), (3, 4)]"
+ ]
+ },
+ "execution_count": 55,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "gap=5\n",
+ "[(items[i//2], items[i//2+gap]) for i in range(0, len(items), 2)]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 91,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "c7bs = sanitise(c7b)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 115,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "def bifid_break_mp(message, wordlist=keywords, fitness=Pletters,\n",
+ " number_of_solutions=1, chunksize=500):\n",
+ " \"\"\"Breaks a keyword substitution cipher using a dictionary and\n",
+ " frequency analysis\n",
+ "\n",
+ " >>> keyword_break_mp(keyword_encipher('this is a test message for the ' \\\n",
+ " 'keyword decipherment', 'elephant', KeywordWrapAlphabet.from_last), \\\n",
+ " wordlist=['cat', 'elephant', 'kangaroo']) # doctest: +ELLIPSIS\n",
+ " (('elephant', <KeywordWrapAlphabet.from_last: 2>), -52.834575011...)\n",
+ " >>> keyword_break_mp(keyword_encipher('this is a test message for the ' \\\n",
+ " 'keyword decipherment', 'elephant', KeywordWrapAlphabet.from_last), \\\n",
+ " wordlist=['cat', 'elephant', 'kangaroo'], \\\n",
+ " number_of_solutions=2) # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE\n",
+ " [(('elephant', <KeywordWrapAlphabet.from_last: 2>), -52.834575011...), \n",
+ " (('elephant', <KeywordWrapAlphabet.from_largest: 3>), -52.834575011...)]\n",
+ " \"\"\"\n",
+ " with Pool() as pool:\n",
+ " helper_args = [(message, word, wrap, fitness)\n",
+ " for word in wordlist\n",
+ " for wrap in KeywordWrapAlphabet]\n",
+ " # Gotcha: the helper function here needs to be defined at the top level\n",
+ " # (limitation of Pool.starmap)\n",
+ " breaks = pool.starmap(bifid_break_worker, helper_args, chunksize)\n",
+ " if number_of_solutions == 1:\n",
+ " return max(breaks, key=lambda k: k[1])\n",
+ " else:\n",
+ " return sorted(breaks, key=lambda k: k[1], reverse=True)[:number_of_solutions]\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 116,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "def bifid_break_worker(message, keyword, wrap_alphabet, fitness):\n",
+ " plaintext = bifid_decipher(message, keyword, wrap_alphabet)\n",
+ " fit = fitness(plaintext)\n",
+ " logger.debug('Keyword break attempt using key {0} (wrap={1}) gives fit of '\n",
+ " '{2} and decrypt starting: {3}'.format(keyword, \n",
+ " wrap_alphabet, fit, sanitise(plaintext)[:50]))\n",
+ " return (keyword, wrap_alphabet), fit"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 107,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'enamokkneogiyegrkcuzbgsydkoqoswiwvtgbolrkfuzbgsyskdqusgnttqetuonyegyfkbsteqeycgbudbvqadcepgqrsbbeaeoqilrqcsosfcdyrbztiuirvqrtcmesbkudboeytksofknyegrambmctvxeogttfggemokopiqwinutqhdtoftsgsathnemlteprmrqbstdolsaklrueucsvncyhgqqcsfqlutsdxzthnfuvotauhnyegosloeogwrrqclelbonknefqkrkofvoqhxttvrimhyttvyqosrlegqtbeyroeuegbtnqkeecgqepblclvutouaehtoekceqgpeobwaohndxlstmvnvalttupquvoieruortugrhfsyqosnsqcesrvhtcrarvqnshkudbistnbwuootauhtqefiolctxqoqhdsmrneettrtberyybtnqblqxgrtrveqyfoboxwaehwlplqrcbiowhirimheyotqcciorhitvdaqkdurimhtheslelwxuooneagedooqlfibrlfhesrpxtgrrbkarhrxqobtogwaehwrimheyotlviqpesoyfkbsteqoviiynstnvhltfgarqostqdfotktpfhlrnadyegrtencsrtltknqffyqsnietwrixhogeqgsooihkiuhtwtonotknenquarhtnerycgicadbschhthlbeurbzpmqkqbsoebweprtepkhtsqhrslbrrefycoisnkumuedqrseqtshftqvftvkntlgbyqbyqosyotbucvtetvqoawhtgniucoadpiqomkeysgcyroeuegbefwimtedcpqcyogakzhbnepcztbqoviiotcnguiocdaipkqbkebwyqosepuqsrecnfsvedoipoqkmyegsqdsaogktgniurofkwfldeoupsqerncsfevoyqosxcoueswnfoqkspkbnyrheuqxotktarhasoiofnqhtokluoqivslbqhbcveqberoaboskskcsfslctsgkapbqftvuiilvcsbkaqlbrrubwtgtnkdboskylzlqqyetqekleuebrsyspnbrcfqspstdntrndsichescznbprqealulhteroctydoocwanhtprnocothnypoqysosniltodcsfyvvolwaehwdpiqoskedwonrtentycobwanelolftbnneksonwlhrsqcqqcqrsopeckrcountigqtldycoisnkuotktanhetwklvshfspkboxkqaolkmyegdqossdcorqoszoowaohabmityghiurocczicttqkifbboekyorhehedkxrobesooztmbqnsbtsqcnkgqnxcorruhokkaergezpctbpdnntqqshcqaehrfyvenwqtttbgsrcfvqasarhfksbkufvvawlacteqtfnvctvhspkqwyocnrtormzdnckouekbomkttarlptmroyketcbrusoeqystofbqoskctenquekbkybgtfrbktbxsqesswgeysggrqfsswgeedoovxaiqvdabaginnrptyqoqesomudleoylstoqtodcoawhkybgeukqdgogzxeiexrinpchoawheewgepth'"
+ ]
+ },
+ "execution_count": 107,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "c7bs = sanitise(c7b)\n",
+ "c7br = cat(reversed(c7bs))\n",
+ "c7br"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 148,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(('ligo', <KeywordWrapAlphabet.from_a: 1>), -2505.924490942904)"
+ ]
+ },
+ "execution_count": 148,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "bifid_break_mp(c7bs, wordlist=['gravity', 'ligo'])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 102,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'ksotagstmczesqstldwfasoehepicltaryruvgstiwbtylwzlanehrdmthhlqzeohpsdytllgdxfcetbiislqetoukobnterkoyonsetkodhtymxuefpdtnhnsulwnnurhiotctcrwhprbssrdblxanlrxadxgxatetsegdoeuhawberbaswolpqkrkpfcxufohcyefaeabqtkbrykbdonghsbaodvongcfdvngmeslhetnytkocenotirklsatenkdeeyoentbryuoleqoefcuxpqbsirotbogkvtqbrqgyoqamkninrfottolgmynbsekmeouwueklcpqrekyylvronsntcotrrctdvoyfthkgalscldypooicxrtpdyttohfoqtprrbgtwepsycwpswuylkedbiglsylbctcfecisumvrbyparteagabdqouuttohvbtcdtxczusxrtleburbtkapmsfctmokootcoibkclbetoaralxzdnlpanenadkhhgtsldnyrupnqsravhtpohmplgtaacuhfpttdebroaqhedgvooyyneoebrfudfodroyklhsheqheeqhdinusytmhdqqedsbbdzcylgukonttacivvvcrprteautwrxhdmczntnixhzbeasmboscsyeqdtsxxeiodohrnofaidlbabrobumelkaeuvnlylglqnfpeqklhwlqeselhameievlbeawrlnllyetoeolencrduoghqqoeqyhlqidrrvndrrwnfhmottqllpayunortyoeariuhharstrhnsfaaoqlipqkohcrnldicnlshnysnrtdbiggeonatcseqosygonehtdutacbzdbstdcrzttntrbtunrotcuewfslftkgdruetlrxrgbmvegfsqieybgqtfxaxrvqbybcaibhoeoolnpxnrdatsspxotloerkwotcheutoerrufnprncktohsqarexdccnbtbekxtqtcrtbaqsottmbltovlurbeoolrtpksbtpyvrasrbtkfricyeremtpaqunucemnterrmdpoldyaicofeoppgepxtdaioeesqqysthohkeotktnstxntgtmhqvyhoythkeanebdshlmtrnqhrunweeeozctiofegqolrfmmdbdacryrmqrypwuwvcntdyqksdamrsglgisanncrmoerfveprpkgbagkerobderbnbatdnedugenxarredlduheegqbrycawnknbnylomloetokdolqreyuecvufbrpsmsptadqthkuotdvknhuyetldctwotidfglrgspmhokusbvtpvbeietnxqbirwhspqetmyotewabodyfppaoacoequgsrrgtyqfsnegmtfvzelmfwosrutwpvnamanthhgcnepsepeguldrhaenwolwhhohnsrlpxnsdhenvadcbyqicaboptfaoknvcmeoerqbtlyovbbddommednhlmrlcyaeflratepytylrnpcantuepwpxxanfthsdnowzirihfqqcedlewwhkcelinfwniiohclardlbqqokzrwvdswbufemcsqqveqnbruynipgrbaytsqkkkyodugayche'"
+ ]
+ },
+ "execution_count": 102,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "bifid_decipher(c7bs, 'capris', KeywordWrapAlphabet.from_a )"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 104,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'dnrobchyoikvkwtucnsiganmyoanfatckweqpwxwehfdpoxqdvtworugsnpsxanmycvirrgedmuihpienwfnpwyzdffaqsxsoutvbvqlovoplenqrnktqlernruwptiswodnhaxomrtwbmpunnbnolcrvsasmcblsvawegytshecczeperucfeqlrcosbfdhdkcaeipnsligmsnapleqpoutoqgtcobyzorcehvvkkrhoxngkavnolkcrncshwetpocgnysxewemonekysintysuqrlntykpvsckgenbecfybfmycsrtzrxfckstgbirtnmnhdhcetfvuttwptpbigplyctfisoxttslhhbvtnotminnusfcqobdtnlhnpbnhxhpirckoatchwiaofaloprrbyonlouscekwlsnboyciswcoosyirodpwsgghcqhofeuosmtqfhqsztrsscwxfzwrnhhnphtpvwnurikaeoxgftoyodrmaqnosloukciskmbycicidsgeofsbrfodhsrtskwtpbtgnsmnyncrvsrhtwrsiolhlylrnntvrkenffvgfypknntxryqqgonspndmocrhcpfrnbgerwqncuiciqverfealtrnoomnwdnenepldpgatsbbffsaogoynownnotoxbeckllrnonbknycsensfleqbctonegzaccsifmnuezvlfqsurrgwviiuwrdcgoininoyseugowzkpntfctreowotnetkswlctahmgrpoypohsnoqnqooogboctspteznllttcurbcbiewnslipsshliwsybvalnlosrrtpcfzepwsnonktceovhhrnqfeilrkmsrlseoinyfsfunulffevuofwrenqbrettkrtkbnkelciibvsysafkrisombfmsqgwlfbnekikdyreipgzshnonclsrzgyceeanhlvcluucfsomraasehigprxbmfiftdnhgxhfbnzopntrsgcudoigstteflifktxiewbaqltwevuznctfgxhgtihgeruomubtgsvaxgoysnontudtebmabnbvsnsrqffslnigcfnemqgnhfckqpncoewfrnmbictedfkwaateghravmulprcftrqngazecectflxcicnhhwllbrwpoiitgqvknmogoeckpsqtvofttwbhpsntarshokvnigrlypropqiitoznlghoknmifdedtapmpisprrsfewfnqttitvnkoaltfmfqicnsaedyxuaklctantctroesoorbkkmpktnwnoulfnmrvougqstqkfdtttvarerhylgfoimeanomleupotornghfryklsyfgtnxdnnsttsoitriyisennougsveatellinkpetkaxodulaihaoebevagqodofghminllhpelcnszrbagvzsclxphrvplbhossnckahwaeroakctnekodiwgfinquogmgraqpgqafienectgnwoeusnilosiptysyfxuydrdxsgtcoucislntosflhttnogzrlntrwkrxiokklphbagvsufdlxpuhpnoqwuukirefqweuxtrtbtnnwrshqneawdghirfaturhpwesptebb'"
+ ]
+ },
+ "execution_count": 104,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "bifid_decipher(c7br, 'trinket', KeywordWrapAlphabet.from_a)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.5.2"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
{
- "metadata": {
- "name": "",
- "signature": "sha256:112d1c84c318592f927e18c5b0f15ed60ac8418ca15cb79596ba6212ff2d7e3f"
- },
- "nbformat": 3,
- "nbformat_minor": 0,
- "worksheets": [
+ "cells": [
{
- "cells": [
- {
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "import matplotlib.pyplot as plt\n",
- "import pandas as pd\n",
- "import collections\n",
- "import string\n",
- "import numpy as np\n",
- "from numpy import matrix\n",
- "from numpy import linalg\n",
- "%matplotlib inline\n",
- "\n",
- "from cipher import *\n",
- "from cipherbreak import *\n",
- "\n",
- "c6a = open('2014/6a.ciphertext').read()\n",
- "c6b = open('2014/6b.ciphertext').read()"
- ],
- "language": "python",
- "metadata": {},
- "outputs": [],
- "prompt_number": 54
- },
- {
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "key_a, score = railfence_break(sanitise(c6a))\n",
- "key_a, score"
- ],
- "language": "python",
- "metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 3,
- "text": [
- "(3, -2314.997881051078)"
- ]
- }
- ],
- "prompt_number": 3
- },
- {
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "' '.join(segment(railfence_decipher(sanitise(c6a), key_a)))"
- ],
- "language": "python",
- "metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 4,
- "text": [
- "'mark the last message told usa lot the scuttling equipment is designed to pump water in and out of the vessel like a submarine dive control but clearly they werent planning to turn a container ship into a sub this ship is a largescale version of something i have seen in the caribbean drug runners use a similar technique to get below radar coverage for inshore runs sinking the vessel so that the deck remains just below the wave tops the fda pirates seem more interested in staying away from shore but getting close enough to track and record electronic communications without detection i am guessing this scuttling system is what they call nautilus in their log but i am still baffled by the references to seahorse the next page of the log looks harder to crack but the cipher clerk tells me it is a hill cipher and that they must have been in a hurry or have been enciphering by hand since they just used a two by two matrix actually we have been pretty lax with our security and i think the next message is end will use avi genere cipher given that we are using secure cables i dont think we have too much to worry about so i will keep the keyword short say three characters more later harry'"
- ]
- }
- ],
- "prompt_number": 4
- },
+ "cell_type": "code",
+ "execution_count": 54,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "import matplotlib.pyplot as plt\n",
+ "import pandas as pd\n",
+ "import collections\n",
+ "import string\n",
+ "import numpy as np\n",
+ "from numpy import matrix\n",
+ "from numpy import linalg\n",
+ "%matplotlib inline\n",
+ "\n",
+ "from cipher import *\n",
+ "from cipherbreak import *\n",
+ "\n",
+ "c6a = open('2014/6a.ciphertext').read()\n",
+ "c6b = open('2014/6b.ciphertext').read()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "c6bs = sanitise(c6b)\n",
- "c6bs"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "(3, -2314.997881051078)"
+ ]
+ },
+ "execution_count": 3,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 7,
- "text": [
- "'hwssswxfewhhrfewpdrvttdhxbccleayphalnadhiehaoudrotwnrrvysabjlttbaytmelrkaidopthatlelrtwaamaneksvvzrvllatkcrjquicizgtoqcpnrrkttowandqehtqrvtbaydqealannohulanuzlwextlvjrvivhnohdqmgykaclmswrupdetfioftfelhzpxhaswftwprrsweiseohefpdrvttnvagdvswgoerbetnharvaeevtlltbmgaiatgelinmdawevhatterdhrznbnvoutnefoteveaehlaymhacglzeptvvdimworfisgtuzlwibeqohubtghamqornjnnrumqvjtxeltfovgawdaeevllgrtxibgtibevmpsaateoasevaeyqohameonncfuidoefafattemuimnflznbekofobrliaehhauihnnnwzaeevtlltpaalnanvtzlzuucptaelinanpaahewfthaosetaribnbnvhaevdhyytlmuxb'"
- ]
- }
- ],
- "prompt_number": 7
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "key_a, score = railfence_break(sanitise(c6a))\n",
+ "key_a, score"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "c6b_nums = [ord(c) - ord('a') for c in c6bs]\n",
- "c6b_nums"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "'mark the last message told usa lot the scuttling equipment is designed to pump water in and out of the vessel like a submarine dive control but clearly they werent planning to turn a container ship into a sub this ship is a largescale version of something i have seen in the caribbean drug runners use a similar technique to get below radar coverage for inshore runs sinking the vessel so that the deck remains just below the wave tops the fda pirates seem more interested in staying away from shore but getting close enough to track and record electronic communications without detection i am guessing this scuttling system is what they call nautilus in their log but i am still baffled by the references to seahorse the next page of the log looks harder to crack but the cipher clerk tells me it is a hill cipher and that they must have been in a hurry or have been enciphering by hand since they just used a two by two matrix actually we have been pretty lax with our security and i think the next message is end will use avi genere cipher given that we are using secure cables i dont think we have too much to worry about so i will keep the keyword short say three characters more later harry'"
+ ]
+ },
+ "execution_count": 4,
"metadata": {},
- "outputs": [
- {
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- "output_type": "pyout",
- "prompt_number": 17,
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- ],
- "prompt_number": 17
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "' '.join(segment(railfence_decipher(sanitise(c6a), key_a)))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "m = np.matrix([[7,8], [11,11]])\n",
- "m"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "'hwssswxfewhhrfewpdrvttdhxbccleayphalnadhiehaoudrotwnrrvysabjlttbaytmelrkaidopthatlelrtwaamaneksvvzrvllatkcrjquicizgtoqcpnrrkttowandqehtqrvtbaydqealannohulanuzlwextlvjrvivhnohdqmgykaclmswrupdetfioftfelhzpxhaswftwprrsweiseohefpdrvttnvagdvswgoerbetnharvaeevtlltbmgaiatgelinmdawevhatterdhrznbnvoutnefoteveaehlaymhacglzeptvvdimworfisgtuzlwibeqohubtghamqornjnnrumqvjtxeltfovgawdaeevllgrtxibgtibevmpsaateoasevaeyqohameonncfuidoefafattemuimnflznbekofobrliaehhauihnnnwzaeevtlltpaalnanvtzlzuucptaelinanpaahewfthaosetaribnbnvhaevdhyytlmuxb'"
+ ]
+ },
+ "execution_count": 7,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 106,
- "text": [
- "matrix([[ 7, 8],\n",
- " [11, 11]])"
- ]
- }
- ],
- "prompt_number": 106
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "c6bs = sanitise(c6b)\n",
+ "c6bs"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "np.linalg.det(m)"
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- "language": "python",
+ "data": {
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+ },
+ "execution_count": 17,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 107,
- "text": [
- "-11.000000000000002"
- ]
- }
- ],
- "prompt_number": 107
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "c6b_nums = [ord(c) - ord('a') for c in c6bs]\n",
+ "c6b_nums"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 106,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "m.I"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "matrix([[ 7, 8],\n",
+ " [11, 11]])"
+ ]
+ },
+ "execution_count": 106,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 108,
- "text": [
- "matrix([[-1. , 0.72727273],\n",
- " [ 1. , -0.63636364]])"
- ]
- }
- ],
- "prompt_number": 108
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "m = np.matrix([[7,8], [11,11]])\n",
+ "m"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 107,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "v = np.matrix([[7], [22]])\n",
- "v"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "-11.000000000000002"
+ ]
+ },
+ "execution_count": 107,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 37,
- "text": [
- "matrix([[ 7],\n",
- " [22]])"
- ]
- }
- ],
- "prompt_number": 37
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "np.linalg.det(m)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 108,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "c = (m*v) % 26\n",
- "c"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "matrix([[-1. , 0.72727273],\n",
+ " [ 1. , -0.63636364]])"
+ ]
+ },
+ "execution_count": 108,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 46,
- "text": [
- "matrix([[9],\n",
- " [5]])"
- ]
- }
- ],
- "prompt_number": 46
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "m.I"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 37,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "np.linalg.solve(m, c) % 26"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "matrix([[ 7],\n",
+ " [22]])"
+ ]
+ },
+ "execution_count": 37,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 48,
- "text": [
- "matrix([[ 7.],\n",
- " [ 22.]])"
- ]
- }
- ],
- "prompt_number": 48
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "v = np.matrix([[7], [22]])\n",
+ "v"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 46,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "m*v"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "matrix([[9],\n",
+ " [5]])"
+ ]
+ },
+ "execution_count": 46,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 40,
- "text": [
- "matrix([[ 87],\n",
- " [109]])"
- ]
- }
- ],
- "prompt_number": 40
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "c = (m*v) % 26\n",
+ "c"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 48,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "(m*v)%26"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "matrix([[ 7.],\n",
+ " [ 22.]])"
+ ]
+ },
+ "execution_count": 48,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 41,
- "text": [
- "matrix([[9],\n",
- " [5]])"
- ]
- }
- ],
- "prompt_number": 41
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "np.linalg.solve(m, c) % 26"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 40,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "np.linalg.solve(m, (m*v)%26)%26"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "matrix([[ 87],\n",
+ " [109]])"
+ ]
+ },
+ "execution_count": 40,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 42,
- "text": [
- "matrix([[ 7.],\n",
- " [ 22.]])"
- ]
- }
- ],
- "prompt_number": 42
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "m*v"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 41,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "len(m)"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "matrix([[9],\n",
+ " [5]])"
+ ]
+ },
+ "execution_count": 41,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 51,
- "text": [
- "2"
- ]
- }
- ],
- "prompt_number": 51
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "(m*v)%26"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 42,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "def hill_encipher(matrix, message_letters, fillvalue='a'):\n",
- " n = len(matrix)\n",
- " sanitised_message = sanitise(message_letters)\n",
- " if len(sanitised_message) % n != 0:\n",
- " padding = fillvalue[0] * (n - len(sanitised_message) % n)\n",
- " else:\n",
- " padding = ''\n",
- " message = [ord(c) - ord('a') for c in sanitised_message + padding]\n",
- " message_chunks = [message[i:i+n] for i in range(0, len(message), n)]\n",
- " # message_chunks = chunks(message, len(matrix), fillvalue=None)\n",
- " enciphered_chunks = [((matrix * np.matrix(c).T).T).tolist()[0] for c in message_chunks]\n",
- " return ''.join([chr(int(round(l)) % 26 + ord('a')) for l in sum(enciphered_chunks, [])])"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "matrix([[ 7.],\n",
+ " [ 22.]])"
+ ]
+ },
+ "execution_count": 42,
"metadata": {},
- "outputs": [],
- "prompt_number": 181
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "np.linalg.solve(m, (m*v)%26)%26"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 51,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "hill_encipher(m, 'hellothere')"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "2"
+ ]
+ },
+ "execution_count": 51,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 156,
- "text": [
- "'drjiqzdrvx'"
- ]
- }
- ],
- "prompt_number": 156
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "len(m)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 181,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "def hill_encipher(matrix, message_letters, fillvalue='a'):\n",
+ " n = len(matrix)\n",
+ " sanitised_message = sanitise(message_letters)\n",
+ " if len(sanitised_message) % n != 0:\n",
+ " padding = fillvalue[0] * (n - len(sanitised_message) % n)\n",
+ " else:\n",
+ " padding = ''\n",
+ " message = [ord(c) - ord('a') for c in sanitised_message + padding]\n",
+ " message_chunks = [message[i:i+n] for i in range(0, len(message), n)]\n",
+ " # message_chunks = chunks(message, len(matrix), fillvalue=None)\n",
+ " enciphered_chunks = [((matrix * np.matrix(c).T).T).tolist()[0] for c in message_chunks]\n",
+ " return ''.join([chr(int(round(l)) % 26 + ord('a')) for l in sum(enciphered_chunks, [])])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 156,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "msg = [ord(c) - ord('a') for c in 'hellothere']\n",
- "msg"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "'drjiqzdrvx'"
+ ]
+ },
+ "execution_count": 156,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 68,
- "text": [
- "[7, 4, 11, 11, 14, 19, 7, 4, 17, 4]"
- ]
- }
- ],
- "prompt_number": 68
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "hill_encipher(m, 'hellothere')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 68,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "msgc = [msg[i:i+len(m)] for i in range(0, len(msg), len(m))]\n",
- "msgc"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "[7, 4, 11, 11, 14, 19, 7, 4, 17, 4]"
+ ]
+ },
+ "execution_count": 68,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 112,
- "text": [
- "[[7, 11], [14, 25], [21, 14], [7, 11], [11, 15], [0, 0]]"
- ]
- }
- ],
- "prompt_number": 112
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "msg = [ord(c) - ord('a') for c in 'hellothere']\n",
+ "msg"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 112,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "((m*np.matrix(msgc[0]).T).T % 26).tolist()[0]"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "[[7, 11], [14, 25], [21, 14], [7, 11], [11, 15], [0, 0]]"
+ ]
+ },
+ "execution_count": 112,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 87,
- "text": [
- "[7, 11]"
- ]
- }
- ],
- "prompt_number": 87
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "msgc = [msg[i:i+len(m)] for i in range(0, len(msg), len(m))]\n",
+ "msgc"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 87,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "def hill_decipher(matrix, message, fillvalue='a'):\n",
- " adjugate = linalg.det(matrix)*linalg.inv(matrix)\n",
- " inverse_determinant = modular_division_table[int(round(linalg.det(matrix))) % 26][1]\n",
- " inverse_matrix = (inverse_determinant * adjugate) % 26\n",
- " return hill_encipher(inverse_matrix, message, fillvalue) "
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "[7, 11]"
+ ]
+ },
+ "execution_count": 87,
"metadata": {},
- "outputs": [],
- "prompt_number": 195
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "((m*np.matrix(msgc[0]).T).T % 26).tolist()[0]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 195,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "def hill_decipher(matrix, message, fillvalue='a'):\n",
+ " adjugate = linalg.det(matrix)*linalg.inv(matrix)\n",
+ " inverse_determinant = modular_division_table[int(round(linalg.det(matrix))) % 26][1]\n",
+ " inverse_matrix = (inverse_determinant * adjugate) % 26\n",
+ " return hill_encipher(inverse_matrix, message, fillvalue) "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 161,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "hill_decipher(m, 'drjiqzdrvx')"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "'hellothere'"
+ ]
+ },
+ "execution_count": 161,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 161,
- "text": [
- "'hellothere'"
- ]
- }
- ],
- "prompt_number": 161
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "hill_decipher(m, 'drjiqzdrvx')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 114,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "msg = [ord(c) - ord('a') for c in 'drjiqzdrvxaa']\n",
- "msg"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "[3, 17, 9, 8, 16, 25, 3, 17, 21, 23, 0, 0]"
+ ]
+ },
+ "execution_count": 114,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 114,
- "text": [
- "[3, 17, 9, 8, 16, 25, 3, 17, 21, 23, 0, 0]"
- ]
- }
- ],
- "prompt_number": 114
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "msg = [ord(c) - ord('a') for c in 'drjiqzdrvxaa']\n",
+ "msg"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 115,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "msgc = [msg[i:i+len(m)] for i in range(0, len(msg), len(m))]\n",
- "msgc"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "[[3, 17], [9, 8], [16, 25], [3, 17], [21, 23], [0, 0]]"
+ ]
+ },
+ "execution_count": 115,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 115,
- "text": [
- "[[3, 17], [9, 8], [16, 25], [3, 17], [21, 23], [0, 0]]"
- ]
- }
- ],
- "prompt_number": 115
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "msgc = [msg[i:i+len(m)] for i in range(0, len(msg), len(m))]\n",
+ "msgc"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 116,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "(np.linalg.solve(m, np.matrix(msgc[0]).T).T % 26)"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "matrix([[ 9.36363636, 18.18181818]])"
+ ]
+ },
+ "execution_count": 116,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 116,
- "text": [
- "matrix([[ 9.36363636, 18.18181818]])"
- ]
- }
- ],
- "prompt_number": 116
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "(np.linalg.solve(m, np.matrix(msgc[0]).T).T % 26)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 142,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "m_adj = linalg.det(m)*linalg.inv(m)\n",
- "m_adj"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "matrix([[ 11., -8.],\n",
+ " [-11., 7.]])"
+ ]
+ },
+ "execution_count": 142,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 142,
- "text": [
- "matrix([[ 11., -8.],\n",
- " [-11., 7.]])"
- ]
- }
- ],
- "prompt_number": 142
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "m_adj = linalg.det(m)*linalg.inv(m)\n",
+ "m_adj"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 148,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "modular_division_table[int(round(linalg.det(m))) % 26][1]"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "7"
+ ]
+ },
+ "execution_count": 148,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 148,
- "text": [
- "7"
- ]
- }
- ],
- "prompt_number": 148
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "modular_division_table[int(round(linalg.det(m))) % 26][1]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 150,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "m_inv = (modular_division_table[int(round(linalg.det(m))) % 26][1] * m_adj) % 26\n",
- "m_inv"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "matrix([[ 25., 22.],\n",
+ " [ 1., 23.]])"
+ ]
+ },
+ "execution_count": 150,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 150,
- "text": [
- "matrix([[ 25., 22.],\n",
- " [ 1., 23.]])"
- ]
- }
- ],
- "prompt_number": 150
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "m_inv = (modular_division_table[int(round(linalg.det(m))) % 26][1] * m_adj) % 26\n",
+ "m_inv"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 157,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "hill_encipher(m_inv, 'drjiqzdrvx')"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "'hellothere'"
+ ]
+ },
+ "execution_count": 157,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 157,
- "text": [
- "'hellothere'"
- ]
- }
- ],
- "prompt_number": 157
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "hill_encipher(m_inv, 'drjiqzdrvx')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 120,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "np.dot(m , 1/linalg.det(m) * mc)"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "matrix([[ 1., 0.],\n",
+ " [ 0., 1.]])"
+ ]
+ },
+ "execution_count": 120,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 120,
- "text": [
- "matrix([[ 1., 0.],\n",
- " [ 0., 1.]])"
- ]
- }
- ],
- "prompt_number": 120
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "np.dot(m , 1/linalg.det(m) * mc)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 122,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "ml = np.matrix([[6, 24, 1], [13, 16, 10], [20, 17, 15]])\n",
- "ml"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "matrix([[ 6, 24, 1],\n",
+ " [13, 16, 10],\n",
+ " [20, 17, 15]])"
+ ]
+ },
+ "execution_count": 122,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 122,
- "text": [
- "matrix([[ 6, 24, 1],\n",
- " [13, 16, 10],\n",
- " [20, 17, 15]])"
- ]
- }
- ],
- "prompt_number": 122
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "ml = np.matrix([[6, 24, 1], [13, 16, 10], [20, 17, 15]])\n",
+ "ml"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 137,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "ml_adj = linalg.det(ml)*linalg.inv(ml) % 26\n",
- "ml_adj"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "matrix([[ 18., 21., 16.],\n",
+ " [ 5., 18., 5.],\n",
+ " [ 5., 14., 18.]])"
+ ]
+ },
+ "execution_count": 137,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 137,
- "text": [
- "matrix([[ 18., 21., 16.],\n",
- " [ 5., 18., 5.],\n",
- " [ 5., 14., 18.]])"
- ]
- }
- ],
- "prompt_number": 137
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "ml_adj = linalg.det(ml)*linalg.inv(ml) % 26\n",
+ "ml_adj"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 138,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "modular_division_table[int(linalg.det(ml) % 26)][1]"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "25"
+ ]
+ },
+ "execution_count": 138,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 138,
- "text": [
- "25"
- ]
- }
- ],
- "prompt_number": 138
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "modular_division_table[int(linalg.det(ml) % 26)][1]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 139,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "ml_inv = (modular_division_table[int(linalg.det(ml) % 26)][1] * ml_adj) % 26\n",
- "ml_inv"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "matrix([[ 8., 5., 10.],\n",
+ " [ 21., 8., 21.],\n",
+ " [ 21., 12., 8.]])"
+ ]
+ },
+ "execution_count": 139,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 139,
- "text": [
- "matrix([[ 8., 5., 10.],\n",
- " [ 21., 8., 21.],\n",
- " [ 21., 12., 8.]])"
- ]
- }
- ],
- "prompt_number": 139
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "ml_inv = (modular_division_table[int(linalg.det(ml) % 26)][1] * ml_adj) % 26\n",
+ "ml_inv"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 193,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "hill_encipher(ml, 'hello there')"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "'tfjflpznvyac'"
+ ]
+ },
+ "execution_count": 193,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 193,
- "text": [
- "'tfjflpznvyac'"
- ]
- }
- ],
- "prompt_number": 193
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "hill_encipher(ml, 'hello there')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 196,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "hill_decipher(ml, 'tfjflpznvyac')"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "'hellothereaa'"
+ ]
+ },
+ "execution_count": 196,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 196,
- "text": [
- "'hellothereaa'"
- ]
- }
- ],
- "prompt_number": 196
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "hill_decipher(ml, 'tfjflpznvyac')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 182,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "hill_encipher(ml, 'act')"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "'poh'"
+ ]
+ },
+ "execution_count": 182,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 182,
- "text": [
- "'poh'"
- ]
- }
- ],
- "prompt_number": 182
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "hill_encipher(ml, 'act')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 192,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "hill_decipher(ml, 'poh')"
- ],
- "language": "python",
- "metadata": {},
- "outputs": [
- {
- "output_type": "stream",
- "stream": "stdout",
- "text": [
- "[[ 8. 5. 10.]\n",
- " [ 21. 8. 21.]\n",
- " [ 21. 12. 8.]]\n"
- ]
- },
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 192,
- "text": [
- "'act'"
- ]
- }
- ],
- "prompt_number": 192
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[[ 8. 5. 10.]\n",
+ " [ 21. 8. 21.]\n",
+ " [ 21. 12. 8.]]\n"
+ ]
},
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "[chr(int(round(i)) % 26 + ord('a')) for i in (ml_inv * np.matrix([ord(c) - ord('a') for c in 'poh']).T).T.tolist()[0]]"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "'act'"
+ ]
+ },
+ "execution_count": 192,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 180,
- "text": [
- "['a', 'c', 't']"
- ]
- }
- ],
- "prompt_number": 180
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "hill_decipher(ml, 'poh')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 180,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "hill_encipher(ml_inv, 'poh')"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "['a', 'c', 't']"
+ ]
+ },
+ "execution_count": 180,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 184,
- "text": [
- "'act'"
- ]
- }
- ],
- "prompt_number": 184
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "[chr(int(round(i)) % 26 + ord('a')) for i in (ml_inv * np.matrix([ord(c) - ord('a') for c in 'poh']).T).T.tolist()[0]]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 184,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "len([list(m) for m in itertools.product([list(r) for r in itertools.product(range(26), repeat=3)], repeat=3)])"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "'act'"
+ ]
+ },
+ "execution_count": 184,
"metadata": {},
- "outputs": [
- {
- "ename": "KeyboardInterrupt",
- "evalue": "",
- "output_type": "pyerr",
- "traceback": [
- "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
- "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
- ]
- }
- ],
- "prompt_number": 203
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "hill_encipher(ml_inv, 'poh')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 203,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "(3**3)**3"
- ],
- "language": "python",
- "metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 202,
- "text": [
- "19683"
- ]
- }
- ],
- "prompt_number": 202
- },
+ "ename": "KeyboardInterrupt",
+ "evalue": "",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
+ "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
+ ]
+ }
+ ],
+ "source": [
+ "len([list(m) for m in itertools.product([list(r) for r in itertools.product(range(26), repeat=3)], repeat=3)])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 202,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "[np.matrix(list(m)) for m in itertools.product([list(r) for r in itertools.product(range(3), repeat=2)], repeat=2)]"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "19683"
+ ]
+ },
+ "execution_count": 202,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 206,
- "text": [
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- " [0, 0]]), matrix([[2, 2],\n",
- " [0, 1]]), matrix([[2, 2],\n",
- " [0, 2]]), matrix([[2, 2],\n",
- " [1, 0]]), matrix([[2, 2],\n",
- " [1, 1]]), matrix([[2, 2],\n",
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- " [2, 0]]), matrix([[2, 2],\n",
- " [2, 1]]), matrix([[2, 2],\n",
- " [2, 2]])]"
- ]
- }
- ],
- "prompt_number": 206
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "(3**3)**3"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 206,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "all_matrices = [np.matrix(list(m)) for m in itertools.product([list(r) for r in itertools.product(range(26), repeat=2)], repeat=2)]\n",
- "valid_matrices = [m for m, d in zip(all_matrices, (int(round(linalg.det(m))) for m in all_matrices))\n",
- " if d != 0\n",
- " if d % 2 != 0\n",
- " if d % 13 != 0 ]\n",
- "len(valid_matrices)"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
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+ " [0, 0]]), matrix([[0, 0],\n",
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+ " [2, 0]]), matrix([[0, 0],\n",
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+ " [2, 2]]), matrix([[2, 0],\n",
+ " [0, 0]]), matrix([[2, 0],\n",
+ " [0, 1]]), matrix([[2, 0],\n",
+ " [0, 2]]), matrix([[2, 0],\n",
+ " [1, 0]]), matrix([[2, 0],\n",
+ " [1, 1]]), matrix([[2, 0],\n",
+ " [1, 2]]), matrix([[2, 0],\n",
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+ " [2, 1]]), matrix([[2, 0],\n",
+ " [2, 2]]), matrix([[2, 1],\n",
+ " [0, 0]]), matrix([[2, 1],\n",
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+ " [0, 2]]), matrix([[2, 1],\n",
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+ " [0, 2]]), matrix([[2, 2],\n",
+ " [1, 0]]), matrix([[2, 2],\n",
+ " [1, 1]]), matrix([[2, 2],\n",
+ " [1, 2]]), matrix([[2, 2],\n",
+ " [2, 0]]), matrix([[2, 2],\n",
+ " [2, 1]]), matrix([[2, 2],\n",
+ " [2, 2]])]"
+ ]
+ },
+ "execution_count": 206,
"metadata": {},
- "outputs": [
- {
- "metadata": {},
- "output_type": "pyout",
- "prompt_number": 215,
- "text": [
- "157248"
- ]
- }
- ],
- "prompt_number": 215
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "[np.matrix(list(m)) for m in itertools.product([list(r) for r in itertools.product(range(3), repeat=2)], repeat=2)]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 215,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "%%timeit\n",
- "[m for m, d in zip(all_matrices, (int(round(linalg.det(m))) for m in all_matrices))\n",
- " if d != 0\n",
- " if d % 2 != 0\n",
- " if d % 13 != 0 ]\n",
- "print('done')"
- ],
- "language": "python",
+ "data": {
+ "text/plain": [
+ "157248"
+ ]
+ },
+ "execution_count": 215,
"metadata": {},
- "outputs": [
- {
- "output_type": "stream",
- "stream": "stdout",
- "text": [
- "done\n",
- "done"
- ]
- },
- {
- "output_type": "stream",
- "stream": "stdout",
- "text": [
- "\n",
- "done"
- ]
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- "stream": "stdout",
- "text": [
- "\n",
- "done"
- ]
- },
- {
- "output_type": "stream",
- "stream": "stdout",
- "text": [
- "\n",
- "1 loops, best of 3: 10 s per loop\n"
- ]
- }
- ],
- "prompt_number": 216
- },
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "all_matrices = [np.matrix(list(m)) for m in itertools.product([list(r) for r in itertools.product(range(26), repeat=2)], repeat=2)]\n",
+ "valid_matrices = [m for m, d in zip(all_matrices, (int(round(linalg.det(m))) for m in all_matrices))\n",
+ " if d != 0\n",
+ " if d % 2 != 0\n",
+ " if d % 13 != 0 ]\n",
+ "len(valid_matrices)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 216,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [
- "%%timeit\n",
- "[m for m in all_matrices\n",
- " if int(round(linalg.det(m))) != 0\n",
- " if int(round(linalg.det(m))) % 2 != 0\n",
- " if int(round(linalg.det(m))) % 13 != 0 ]\n",
- "print('done')"
- ],
- "language": "python",
- "metadata": {},
- "outputs": [
- {
- "output_type": "stream",
- "stream": "stdout",
- "text": [
- "done\n",
- "done"
- ]
- },
- {
- "output_type": "stream",
- "stream": "stdout",
- "text": [
- "\n",
- "done"
- ]
- },
- {
- "output_type": "stream",
- "stream": "stdout",
- "text": [
- "\n",
- "done"
- ]
- },
- {
- "output_type": "stream",
- "stream": "stdout",
- "text": [
- "\n",
- "1 loops, best of 3: 20.4 s per loop\n"
- ]
- }
- ],
- "prompt_number": 217
- },
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "done\n",
+ "done\n",
+ "done\n",
+ "done\n",
+ "1 loops, best of 3: 10 s per loop\n"
+ ]
+ }
+ ],
+ "source": [
+ "%%timeit\n",
+ "[m for m, d in zip(all_matrices, (int(round(linalg.det(m))) for m in all_matrices))\n",
+ " if d != 0\n",
+ " if d % 2 != 0\n",
+ " if d % 13 != 0 ]\n",
+ "print('done')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 217,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
{
- "cell_type": "code",
- "collapsed": false,
- "input": [],
- "language": "python",
- "metadata": {},
- "outputs": []
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "done\n",
+ "done\n",
+ "done\n",
+ "done\n",
+ "1 loops, best of 3: 20.4 s per loop\n"
+ ]
}
],
- "metadata": {}
+ "source": [
+ "%%timeit\n",
+ "[m for m in all_matrices\n",
+ " if int(round(linalg.det(m))) != 0\n",
+ " if int(round(linalg.det(m))) % 2 != 0\n",
+ " if int(round(linalg.det(m))) % 13 != 0 ]\n",
+ "print('done')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": []
}
- ]
-}
\ No newline at end of file
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.5.2"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
projects / cipher-tools.git / commitdiff