--- /dev/null
+import string
+import collections
+import norms
+import logging
+from itertools import zip_longest, cycle
+from segment import segment
+from multiprocessing import Pool
+
+from cipher import *
+
+# To time a run:
+#
+# import timeit
+# c5a = open('2012/5a.ciphertext', 'r').read()
+# timeit.timeit('keyword_break(c5a)', setup='gc.enable() ; from __main__ import c5a ; from cipher import keyword_break', number=1)
+# timeit.repeat('keyword_break_mp(c5a, chunksize=500)', setup='gc.enable() ; from __main__ import c5a ; from cipher import keyword_break_mp', repeat=5, number=1)
+
+
+english_counts = collections.defaultdict(int)
+with open('count_1l.txt', 'r') as f:
+ for line in f:
+ (letter, count) = line.split("\t")
+ english_counts[letter] = int(count)
+normalised_english_counts = norms.normalise(english_counts)
+
+english_bigram_counts = collections.defaultdict(int)
+with open('count_2l.txt', 'r') as f:
+ for line in f:
+ (bigram, count) = line.split("\t")
+ english_bigram_counts[bigram] = int(count)
+normalised_english_bigram_counts = norms.normalise(english_bigram_counts)
+
+english_trigram_counts = collections.defaultdict(int)
+with open('count_3l.txt', 'r') as f:
+ for line in f:
+ (trigram, count) = line.split("\t")
+ english_trigram_counts[trigram] = int(count)
+normalised_english_trigram_counts = norms.normalise(english_trigram_counts)
+
+
+with open('words.txt', 'r') as f:
+ keywords = [line.rstrip() for line in f]
+
+transpositions = collections.defaultdict(list)
+for word in keywords:
+ transpositions[transpositions_of(word)] += [word]
+
+def frequencies(text):
+ """Count the number of occurrences of each character in text
+
+ >>> sorted(frequencies('abcdefabc').items())
+ [('a', 2), ('b', 2), ('c', 2), ('d', 1), ('e', 1), ('f', 1)]
+ >>> sorted(frequencies('the quick brown fox jumped over the lazy ' \
+ 'dog').items()) # doctest: +NORMALIZE_WHITESPACE
+ [(' ', 8), ('a', 1), ('b', 1), ('c', 1), ('d', 2), ('e', 4), ('f', 1),
+ ('g', 1), ('h', 2), ('i', 1), ('j', 1), ('k', 1), ('l', 1), ('m', 1),
+ ('n', 1), ('o', 4), ('p', 1), ('q', 1), ('r', 2), ('t', 2), ('u', 2),
+ ('v', 1), ('w', 1), ('x', 1), ('y', 1), ('z', 1)]
+ >>> sorted(frequencies('The Quick BROWN fox jumped! over... the ' \
+ '(9lazy) DOG').items()) # doctest: +NORMALIZE_WHITESPACE
+ [(' ', 8), ('!', 1), ('(', 1), (')', 1), ('.', 3), ('9', 1), ('B', 1),
+ ('D', 1), ('G', 1), ('N', 1), ('O', 2), ('Q', 1), ('R', 1), ('T', 1),
+ ('W', 1), ('a', 1), ('c', 1), ('d', 1), ('e', 4), ('f', 1), ('h', 2),
+ ('i', 1), ('j', 1), ('k', 1), ('l', 1), ('m', 1), ('o', 2), ('p', 1),
+ ('r', 1), ('t', 1), ('u', 2), ('v', 1), ('x', 1), ('y', 1), ('z', 1)]
+ >>> sorted(frequencies(sanitise('The Quick BROWN fox jumped! over... ' \
+ 'the (9lazy) DOG')).items()) # doctest: +NORMALIZE_WHITESPACE
+ [('a', 1), ('b', 1), ('c', 1), ('d', 2), ('e', 4), ('f', 1), ('g', 1),
+ ('h', 2), ('i', 1), ('j', 1), ('k', 1), ('l', 1), ('m', 1), ('n', 1),
+ ('o', 4), ('p', 1), ('q', 1), ('r', 2), ('t', 2), ('u', 2), ('v', 1),
+ ('w', 1), ('x', 1), ('y', 1), ('z', 1)]
+ >>> frequencies('abcdefabcdef')['x']
+ 0
+ """
+ #counts = collections.defaultdict(int)
+ #for c in text:
+ # counts[c] += 1
+ #return counts
+ return collections.Counter(c for c in text)
+letter_frequencies = frequencies
+
+
+
+def caesar_break(message,
+ metric=norms.euclidean_distance,
+ target_counts=normalised_english_counts,
+ message_frequency_scaling=norms.normalise):
+ """Breaks a Caesar cipher using frequency analysis
+
+ >>> caesar_break('ibxcsyorsaqcheyklxivoexlevmrimwxsfiqevvmihrsasrxliwyrh' \
+ 'ecjsppsamrkwleppfmergefifvmhixscsymjcsyqeoixlm') # doctest: +ELLIPSIS
+ (4, 0.31863952890183...)
+ >>> caesar_break('wxwmaxdgheetgwuxztgptedbgznitgwwhpguxyhkxbmhvvtlbhgtee' \
+ 'raxlmhiixweblmxgxwmhmaxybkbgztgwztsxwbgmxgmert') # doctest: +ELLIPSIS
+ (19, 0.42152901235832...)
+ >>> caesar_break('yltbbqnqnzvguvaxurorgenafsbezqvagbnornfgsbevpnaabjurer' \
+ 'svaquvzyvxrnznazlybequrvfohgriraabjtbaruraprur') # doctest: +ELLIPSIS
+ (13, 0.316029208075451...)
+ """
+ sanitised_message = sanitise(message)
+ best_shift = 0
+ best_fit = float("inf")
+ for shift in range(26):
+ plaintext = caesar_decipher(sanitised_message, shift)
+ counts = message_frequency_scaling(letter_frequencies(plaintext))
+ fit = metric(target_counts, counts)
+ logger.debug('Caesar break attempt using key {0} gives fit of {1} '
+ 'and decrypt starting: {2}'.format(shift, fit, plaintext[:50]))
+ if fit < best_fit:
+ best_fit = fit
+ best_shift = shift
+ logger.info('Caesar break best fit: key {0} gives fit of {1} and '
+ 'decrypt starting: {2}'.format(best_shift, best_fit,
+ caesar_decipher(sanitised_message, best_shift)[:50]))
+ return best_shift, best_fit
+
+def affine_break(message,
+ metric=norms.euclidean_distance,
+ target_counts=normalised_english_counts,
+ message_frequency_scaling=norms.normalise):
+ """Breaks an affine cipher using frequency analysis
+
+ >>> affine_break('lmyfu bkuusd dyfaxw claol psfaom jfasd snsfg jfaoe ls ' \
+ 'omytd jlaxe mh jm bfmibj umis hfsul axubafkjamx. ls kffkxwsd jls ' \
+ 'ofgbjmwfkiu olfmxmtmwaokttg jlsx ls kffkxwsd jlsi zg tsxwjl. jlsx ' \
+ 'ls umfjsd jlsi zg hfsqysxog. ls dmmdtsd mx jls bats mh bkbsf. ls ' \
+ 'bfmctsd kfmyxd jls lyj, mztanamyu xmc jm clm cku tmmeaxw kj lai kxd ' \
+ 'clm ckuxj.') # doctest: +ELLIPSIS
+ ((15, 22, True), 0.23570361818655...)
+ """
+ sanitised_message = sanitise(message)
+ best_multiplier = 0
+ best_adder = 0
+ best_one_based = True
+ best_fit = float("inf")
+ for one_based in [True, False]:
+ for multiplier in range(1, 26, 2):
+ for adder in range(26):
+ plaintext = affine_decipher(sanitised_message,
+ multiplier, adder, one_based)
+ counts = message_frequency_scaling(letter_frequencies(plaintext))
+ fit = metric(target_counts, counts)
+ logger.debug('Affine break attempt using key {0}x+{1} ({2}) '
+ 'gives fit of {3} and decrypt starting: {4}'.
+ format(multiplier, adder, one_based, fit,
+ plaintext[:50]))
+ if fit < best_fit:
+ best_fit = fit
+ best_multiplier = multiplier
+ best_adder = adder
+ best_one_based = one_based
+ logger.info('Affine break best fit with key {0}x+{1} ({2}) gives fit of {3} '
+ 'and decrypt starting: {4}'.format(
+ best_multiplier, best_adder, best_one_based, best_fit,
+ affine_decipher(sanitised_message, best_multiplier,
+ best_adder, best_one_based)[:50]))
+ return (best_multiplier, best_adder, best_one_based), best_fit
+
+def keyword_break(message,
+ wordlist=keywords,
+ metric=norms.euclidean_distance,
+ target_counts=normalised_english_counts,
+ message_frequency_scaling=norms.normalise):
+ """Breaks a keyword substitution cipher using a dictionary and
+ frequency analysis
+
+ >>> keyword_break(keyword_encipher('this is a test message for the ' \
+ 'keyword decipherment', 'elephant', 1), \
+ wordlist=['cat', 'elephant', 'kangaroo']) # doctest: +ELLIPSIS
+ (('elephant', 1), 0.41643991598441...)
+ """
+ best_keyword = ''
+ best_wrap_alphabet = True
+ best_fit = float("inf")
+ for wrap_alphabet in range(3):
+ for keyword in wordlist:
+ plaintext = keyword_decipher(message, keyword, wrap_alphabet)
+ counts = message_frequency_scaling(letter_frequencies(plaintext))
+ fit = metric(target_counts, counts)
+ logger.debug('Keyword break attempt using key {0} (wrap={1}) '
+ 'gives fit of {2} and decrypt starting: {3}'.format(
+ keyword, wrap_alphabet, fit,
+ sanitise(plaintext)[:50]))
+ if fit < best_fit:
+ best_fit = fit
+ best_keyword = keyword
+ best_wrap_alphabet = wrap_alphabet
+ logger.info('Keyword break best fit with key {0} (wrap={1}) gives fit of '
+ '{2} and decrypt starting: {3}'.format(best_keyword,
+ best_wrap_alphabet, best_fit, sanitise(
+ keyword_decipher(message, best_keyword,
+ best_wrap_alphabet))[:50]))
+ return (best_keyword, best_wrap_alphabet), best_fit
+
+def keyword_break_mp(message,
+ wordlist=keywords,
+ metric=norms.euclidean_distance,
+ target_counts=normalised_english_counts,
+ message_frequency_scaling=norms.normalise,
+ chunksize=500):
+ """Breaks a keyword substitution cipher using a dictionary and
+ frequency analysis
+
+ >>> keyword_break_mp(keyword_encipher('this is a test message for the ' \
+ 'keyword decipherment', 'elephant', 1), \
+ wordlist=['cat', 'elephant', 'kangaroo']) # doctest: +ELLIPSIS
+ (('elephant', 1), 0.41643991598441...)
+ """
+ with Pool() as pool:
+ helper_args = [(message, word, wrap, metric, target_counts,
+ message_frequency_scaling)
+ for word in wordlist for wrap in range(3)]
+ # Gotcha: the helper function here needs to be defined at the top level
+ # (limitation of Pool.starmap)
+ breaks = pool.starmap(keyword_break_worker, helper_args, chunksize)
+ return min(breaks, key=lambda k: k[1])
+
+def keyword_break_worker(message, keyword, wrap_alphabet, metric, target_counts,
+ message_frequency_scaling):
+ plaintext = keyword_decipher(message, keyword, wrap_alphabet)
+ counts = message_frequency_scaling(letter_frequencies(plaintext))
+ fit = metric(target_counts, counts)
+ logger.debug('Keyword break attempt using key {0} (wrap={1}) gives fit of '
+ '{2} and decrypt starting: {3}'.format(keyword,
+ wrap_alphabet, fit, sanitise(plaintext)[:50]))
+ return (keyword, wrap_alphabet), fit
+
+def scytale_break(message,
+ metric=norms.euclidean_distance,
+ target_counts=normalised_english_bigram_counts,
+ message_frequency_scaling=norms.normalise):
+ """Breaks a Scytale cipher
+
+ >>> scytale_break('tfeulchtrtteehwahsdehneoifeayfsondmwpltmaoalhikotoere' \
+ 'dcweatehiplwxsnhooacgorrcrcraotohsgullasenylrendaianeplscdriioto' \
+ 'aek') # doctest: +ELLIPSIS
+ (6, 0.83453041115025...)
+ """
+ best_key = 0
+ best_fit = float("inf")
+ ngram_length = len(next(iter(target_counts.keys())))
+ for key in range(1, 20):
+ if len(message) % key == 0:
+ plaintext = scytale_decipher(message, key)
+ counts = message_frequency_scaling(frequencies(
+ ngrams(sanitise(plaintext), ngram_length)))
+ fit = metric(target_counts, counts)
+ logger.debug('Scytale break attempt using key {0} gives fit of '
+ '{1} and decrypt starting: {2}'.format(key,
+ fit, sanitise(plaintext)[:50]))
+ if fit < best_fit:
+ best_fit = fit
+ best_key = key
+ logger.info('Scytale break best fit with key {0} gives fit of {1} and '
+ 'decrypt starting: {2}'.format(best_key, best_fit,
+ sanitise(scytale_decipher(message, best_key))[:50]))
+ return best_key, best_fit
+
+def column_transposition_break(message,
+ translist=transpositions,
+ metric=norms.euclidean_distance,
+ target_counts=normalised_english_bigram_counts,
+ message_frequency_scaling=norms.normalise):
+ """Breaks a column transposition cipher using a dictionary and
+ n-gram frequency analysis
+
+ >>> column_transposition_break(column_transposition_encipher(sanitise( \
+ "Turing's homosexuality resulted in a criminal prosecution in 1952, \
+ when homosexual acts were still illegal in the United Kingdom. "), \
+ 'encipher'), \
+ translist={(2, 0, 5, 3, 1, 4, 6): ['encipher'], \
+ (5, 0, 6, 1, 3, 4, 2): ['fourteen'], \
+ (6, 1, 0, 4, 5, 3, 2): ['keyword']}) # doctest: +ELLIPSIS
+ ((2, 0, 5, 3, 1, 4, 6), 0.898128626285...)
+ >>> column_transposition_break(column_transposition_encipher(sanitise( \
+ "Turing's homosexuality resulted in a criminal prosecution in 1952, " \
+ "when homosexual acts were still illegal in the United Kingdom."), \
+ 'encipher'), \
+ translist={(2, 0, 5, 3, 1, 4, 6): ['encipher'], \
+ (5, 0, 6, 1, 3, 4, 2): ['fourteen'], \
+ (6, 1, 0, 4, 5, 3, 2): ['keyword']}, \
+ target_counts=normalised_english_trigram_counts) # doctest: +ELLIPSIS
+ ((2, 0, 5, 3, 1, 4, 6), 1.1958792913127...)
+ """
+ best_transposition = ''
+ best_fit = float("inf")
+ ngram_length = len(next(iter(target_counts.keys())))
+ for transposition in translist.keys():
+ if len(message) % len(transposition) == 0:
+ plaintext = column_transposition_decipher(message, transposition)
+ counts = message_frequency_scaling(frequencies(
+ ngrams(sanitise(plaintext), ngram_length)))
+ fit = metric(target_counts, counts)
+ logger.debug('Column transposition break attempt using key {0} '
+ 'gives fit of {1} and decrypt starting: {2}'.format(
+ translist[transposition][0], fit,
+ sanitise(plaintext)[:50]))
+ if fit < best_fit:
+ best_fit = fit
+ best_transposition = transposition
+ logger.info('Column transposition break best fit with key {0} gives fit '
+ 'of {1} and decrypt starting: {2}'.format(
+ translist[best_transposition][0],
+ best_fit, sanitise(
+ column_transposition_decipher(message,
+ best_transposition))[:50]))
+ return best_transposition, best_fit
+
+
+def column_transposition_break_mp(message,
+ translist=transpositions,
+ metric=norms.euclidean_distance,
+ target_counts=normalised_english_bigram_counts,
+ message_frequency_scaling=norms.normalise,
+ chunksize=500):
+ """Breaks a column transposition cipher using a dictionary and
+ n-gram frequency analysis
+
+ >>> column_transposition_break_mp(column_transposition_encipher(sanitise( \
+ "Turing's homosexuality resulted in a criminal prosecution in 1952, \
+ when homosexual acts were still illegal in the United Kingdom. "), \
+ 'encipher'), \
+ translist={(2, 0, 5, 3, 1, 4, 6): ['encipher'], \
+ (5, 0, 6, 1, 3, 4, 2): ['fourteen'], \
+ (6, 1, 0, 4, 5, 3, 2): ['keyword']}) # doctest: +ELLIPSIS
+ ((2, 0, 5, 3, 1, 4, 6), 0.898128626285...)
+ >>> column_transposition_break_mp(column_transposition_encipher(sanitise( \
+ "Turing's homosexuality resulted in a criminal prosecution in 1952, " \
+ "when homosexual acts were still illegal in the United Kingdom."), \
+ 'encipher'), \
+ translist={(2, 0, 5, 3, 1, 4, 6): ['encipher'], \
+ (5, 0, 6, 1, 3, 4, 2): ['fourteen'], \
+ (6, 1, 0, 4, 5, 3, 2): ['keyword']}, \
+ target_counts=normalised_english_trigram_counts) # doctest: +ELLIPSIS
+ ((2, 0, 5, 3, 1, 4, 6), 1.1958792913127...)
+ """
+ ngram_length = len(next(iter(target_counts.keys())))
+ with Pool() as pool:
+ helper_args = [(message, trans, metric, target_counts, ngram_length,
+ message_frequency_scaling)
+ for trans in translist.keys()]
+ # Gotcha: the helper function here needs to be defined at the top level
+ # (limitation of Pool.starmap)
+ breaks = pool.starmap(column_transposition_break_worker, helper_args, chunksize)
+ return min(breaks, key=lambda k: k[1])
+
+def column_transposition_break_worker(message, transposition, metric, target_counts,
+ ngram_length, message_frequency_scaling):
+ plaintext = column_transposition_decipher(message, transposition)
+ counts = message_frequency_scaling(frequencies(
+ ngrams(sanitise(plaintext), ngram_length)))
+ fit = metric(target_counts, counts)
+ logger.debug('Column transposition break attempt using key {0} '
+ 'gives fit of {1} and decrypt starting: {2}'.format(
+ transposition, fit,
+ sanitise(plaintext)[:50]))
+ return transposition, fit
+
+def vigenere_keyword_break(message,
+ wordlist=keywords,
+ metric=norms.euclidean_distance,
+ target_counts=normalised_english_counts,
+ message_frequency_scaling=norms.normalise):
+ """Breaks a vigenere cipher using a dictionary and
+ frequency analysis
+
+ >>> vigenere_keyword_break(keyword_encipher('this is a test message for the ' \
+ 'keyword decipherment', 'elephant', 1), \
+ wordlist=['cat', 'elephant', 'kangaroo']) # doctest: +ELLIPSIS
+ ('elephant', 0.7166585201707...)
+ """
+ best_keyword = ''
+ best_fit = float("inf")
+ for keyword in wordlist:
+ plaintext = vigenere_decipher(message, keyword)
+ counts = message_frequency_scaling(letter_frequencies(plaintext))
+ fit = metric(target_counts, counts)
+ logger.debug('Vigenere break attempt using key {0} '
+ 'gives fit of {1} and decrypt starting: {2}'.format(
+ keyword, fit,
+ sanitise(plaintext)[:50]))
+ if fit < best_fit:
+ best_fit = fit
+ best_keyword = keyword
+ logger.info('Vigenere break best fit with key {0} gives fit '
+ 'of {1} and decrypt starting: {2}'.format(best_keyword,
+ best_fit, sanitise(
+ vigenere_decipher(message, best_keyword))[:50]))
+ return best_keyword, best_fit
+
+def vigenere_keyword_break_mp(message,
+ wordlist=keywords,
+ metric=norms.euclidean_distance,
+ target_counts=normalised_english_counts,
+ message_frequency_scaling=norms.normalise,
+ chunksize=500):
+ """Breaks a vigenere cipher using a dictionary and
+ frequency analysis
+
+ >>> vigenere_keyword_break_mp(keyword_encipher('this is a test message for the ' \
+ 'keyword decipherment', 'elephant', 1), \
+ wordlist=['cat', 'elephant', 'kangaroo']) # doctest: +ELLIPSIS
+ ('elephant', 0.7166585201707...)
+ """
+ with Pool() as pool:
+ helper_args = [(message, word, metric, target_counts,
+ message_frequency_scaling)
+ for word in wordlist]
+ # Gotcha: the helper function here needs to be defined at the top level
+ # (limitation of Pool.starmap)
+ breaks = pool.starmap(vigenere_keyword_break_worker, helper_args, chunksize)
+ return min(breaks, key=lambda k: k[1])
+
+def vigenere_keyword_break_worker(message, keyword, metric, target_counts,
+ message_frequency_scaling):
+ plaintext = vigenere_decipher(message, keyword)
+ counts = message_frequency_scaling(letter_frequencies(plaintext))
+ fit = metric(target_counts, counts)
+ logger.debug('Vigenere keyword break attempt using key {0} gives fit of '
+ '{1} and decrypt starting: {2}'.format(keyword,
+ fit, sanitise(plaintext)[:50]))
+ return keyword, fit
+
+
+if __name__ == "__main__":
+ import doctest
+ doctest.testmod()
+
import string
import collections
-import norms
+# import norms
import logging
-import math
+# import math
from itertools import zip_longest, repeat, cycle
-from segment import segment
-from multiprocessing import Pool
+# from segment import segment
+# from multiprocessing import Pool
-# To time a run:
-#
-# import timeit
-# c5a = open('2012/5a.ciphertext', 'r').read()
-# timeit.timeit('keyword_break(c5a)', setup='gc.enable() ; from __main__ import c5a ; from cipher import keyword_break', number=1)
-# timeit.repeat('keyword_break_mp(c5a, chunksize=500)', setup='gc.enable() ; from __main__ import c5a ; from cipher import keyword_break_mp', repeat=5, number=1
logger = logging.getLogger(__name__)
logger.addHandler(logging.FileHandler('cipher.log'))
#logger.setLevel(logging.INFO)
#logger.setLevel(logging.DEBUG)
-english_counts = collections.defaultdict(int)
-with open('count_1l.txt', 'r') as f:
- for line in f:
- (letter, count) = line.split("\t")
- english_counts[letter] = int(count)
-normalised_english_counts = norms.normalise(english_counts)
-
-english_bigram_counts = collections.defaultdict(int)
-with open('count_2l.txt', 'r') as f:
- for line in f:
- (bigram, count) = line.split("\t")
- english_bigram_counts[bigram] = int(count)
-normalised_english_bigram_counts = norms.normalise(english_bigram_counts)
-
-english_trigram_counts = collections.defaultdict(int)
-with open('count_3l.txt', 'r') as f:
- for line in f:
- (trigram, count) = line.split("\t")
- english_trigram_counts[trigram] = int(count)
-normalised_english_trigram_counts = norms.normalise(english_trigram_counts)
-
-
-with open('words.txt', 'r') as f:
- keywords = [line.rstrip() for line in f]
modular_division_table = [[0]*26 for x in range(26)]
for a in range(26):
def transpose(items, transposition):
"""Moves items around according to the given transposition
- >>> transpose(['a', 'b', 'c', 'd'], [0,1,2,3])
+ >>> transpose(['a', 'b', 'c', 'd'], (0,1,2,3))
['a', 'b', 'c', 'd']
- >>> transpose(['a', 'b', 'c', 'd'], [3,1,2,0])
+ >>> transpose(['a', 'b', 'c', 'd'], (3,1,2,0))
['d', 'b', 'c', 'a']
- >>> transpose([10,11,12,13,14,15], [3,2,4,1,5,0])
+ >>> transpose([10,11,12,13,14,15], (3,2,4,1,5,0))
[13, 12, 14, 11, 15, 10]
"""
transposed = list(repeat('', len(transposition)))
return transposed
-def frequencies(text):
- """Count the number of occurrences of each character in text
-
- >>> sorted(frequencies('abcdefabc').items())
- [('a', 2), ('b', 2), ('c', 2), ('d', 1), ('e', 1), ('f', 1)]
- >>> sorted(frequencies('the quick brown fox jumped over the lazy ' \
- 'dog').items()) # doctest: +NORMALIZE_WHITESPACE
- [(' ', 8), ('a', 1), ('b', 1), ('c', 1), ('d', 2), ('e', 4), ('f', 1),
- ('g', 1), ('h', 2), ('i', 1), ('j', 1), ('k', 1), ('l', 1), ('m', 1),
- ('n', 1), ('o', 4), ('p', 1), ('q', 1), ('r', 2), ('t', 2), ('u', 2),
- ('v', 1), ('w', 1), ('x', 1), ('y', 1), ('z', 1)]
- >>> sorted(frequencies('The Quick BROWN fox jumped! over... the ' \
- '(9lazy) DOG').items()) # doctest: +NORMALIZE_WHITESPACE
- [(' ', 8), ('!', 1), ('(', 1), (')', 1), ('.', 3), ('9', 1), ('B', 1),
- ('D', 1), ('G', 1), ('N', 1), ('O', 2), ('Q', 1), ('R', 1), ('T', 1),
- ('W', 1), ('a', 1), ('c', 1), ('d', 1), ('e', 4), ('f', 1), ('h', 2),
- ('i', 1), ('j', 1), ('k', 1), ('l', 1), ('m', 1), ('o', 2), ('p', 1),
- ('r', 1), ('t', 1), ('u', 2), ('v', 1), ('x', 1), ('y', 1), ('z', 1)]
- >>> sorted(frequencies(sanitise('The Quick BROWN fox jumped! over... ' \
- 'the (9lazy) DOG')).items()) # doctest: +NORMALIZE_WHITESPACE
- [('a', 1), ('b', 1), ('c', 1), ('d', 2), ('e', 4), ('f', 1), ('g', 1),
- ('h', 2), ('i', 1), ('j', 1), ('k', 1), ('l', 1), ('m', 1), ('n', 1),
- ('o', 4), ('p', 1), ('q', 1), ('r', 2), ('t', 2), ('u', 2), ('v', 1),
- ('w', 1), ('x', 1), ('y', 1), ('z', 1)]
- >>> frequencies('abcdefabcdef')['x']
- 0
- """
- #counts = collections.defaultdict(int)
- #for c in text:
- # counts[c] += 1
- #return counts
- return collections.Counter(c for c in text)
-letter_frequencies = frequencies
def deduplicate(text):
return list(collections.OrderedDict.fromkeys(text))
second column (1) moves to third, the third column (2) moves to second,
and so on.
+ If passed a tuple, assume it's already a transposition and just return it.
+
>>> transpositions_of('clever')
- [0, 2, 1, 4, 3]
- """
- key = deduplicate(keyword)
- transpositions = [key.index(l) for l in sorted(key)]
- return transpositions
+ (0, 2, 1, 4, 3)
+ >>> transpositions_of('fred')
+ (3, 2, 0, 1)
+ >>> transpositions_of((3, 2, 0, 1))
+ (3, 2, 0, 1)
+ """
+ if isinstance(keyword, tuple):
+ return keyword
+ else:
+ key = deduplicate(keyword)
+ transpositions = tuple(key.index(l) for l in sorted(key))
+ return transpositions
def column_transposition_encipher(message, keyword, fillvalue=' '):
"""Enciphers using the column transposition cipher.
-def caesar_break(message,
- metric=norms.euclidean_distance,
- target_counts=normalised_english_counts,
- message_frequency_scaling=norms.normalise):
- """Breaks a Caesar cipher using frequency analysis
-
- >>> caesar_break('ibxcsyorsaqcheyklxivoexlevmrimwxsfiqevvmihrsasrxliwyrh' \
- 'ecjsppsamrkwleppfmergefifvmhixscsymjcsyqeoixlm') # doctest: +ELLIPSIS
- (4, 0.31863952890183...)
- >>> caesar_break('wxwmaxdgheetgwuxztgptedbgznitgwwhpguxyhkxbmhvvtlbhgtee' \
- 'raxlmhiixweblmxgxwmhmaxybkbgztgwztsxwbgmxgmert') # doctest: +ELLIPSIS
- (19, 0.42152901235832...)
- >>> caesar_break('yltbbqnqnzvguvaxurorgenafsbezqvagbnornfgsbevpnaabjurer' \
- 'svaquvzyvxrnznazlybequrvfohgriraabjtbaruraprur') # doctest: +ELLIPSIS
- (13, 0.316029208075451...)
- """
- sanitised_message = sanitise(message)
- best_shift = 0
- best_fit = float("inf")
- for shift in range(26):
- plaintext = caesar_decipher(sanitised_message, shift)
- counts = message_frequency_scaling(letter_frequencies(plaintext))
- fit = metric(target_counts, counts)
- logger.debug('Caesar break attempt using key {0} gives fit of {1} '
- 'and decrypt starting: {2}'.format(shift, fit, plaintext[:50]))
- if fit < best_fit:
- best_fit = fit
- best_shift = shift
- logger.info('Caesar break best fit: key {0} gives fit of {1} and '
- 'decrypt starting: {2}'.format(best_shift, best_fit,
- caesar_decipher(sanitised_message, best_shift)[:50]))
- return best_shift, best_fit
-
-def affine_break(message,
- metric=norms.euclidean_distance,
- target_counts=normalised_english_counts,
- message_frequency_scaling=norms.normalise):
- """Breaks an affine cipher using frequency analysis
-
- >>> affine_break('lmyfu bkuusd dyfaxw claol psfaom jfasd snsfg jfaoe ls ' \
- 'omytd jlaxe mh jm bfmibj umis hfsul axubafkjamx. ls kffkxwsd jls ' \
- 'ofgbjmwfkiu olfmxmtmwaokttg jlsx ls kffkxwsd jlsi zg tsxwjl. jlsx ' \
- 'ls umfjsd jlsi zg hfsqysxog. ls dmmdtsd mx jls bats mh bkbsf. ls ' \
- 'bfmctsd kfmyxd jls lyj, mztanamyu xmc jm clm cku tmmeaxw kj lai kxd ' \
- 'clm ckuxj.') # doctest: +ELLIPSIS
- ((15, 22, True), 0.23570361818655...)
- """
- sanitised_message = sanitise(message)
- best_multiplier = 0
- best_adder = 0
- best_one_based = True
- best_fit = float("inf")
- for one_based in [True, False]:
- for multiplier in range(1, 26, 2):
- for adder in range(26):
- plaintext = affine_decipher(sanitised_message,
- multiplier, adder, one_based)
- counts = message_frequency_scaling(letter_frequencies(plaintext))
- fit = metric(target_counts, counts)
- logger.debug('Affine break attempt using key {0}x+{1} ({2}) '
- 'gives fit of {3} and decrypt starting: {4}'.
- format(multiplier, adder, one_based, fit,
- plaintext[:50]))
- if fit < best_fit:
- best_fit = fit
- best_multiplier = multiplier
- best_adder = adder
- best_one_based = one_based
- logger.info('Affine break best fit with key {0}x+{1} ({2}) gives fit of {3} '
- 'and decrypt starting: {4}'.format(
- best_multiplier, best_adder, best_one_based, best_fit,
- affine_decipher(sanitised_message, best_multiplier,
- best_adder, best_one_based)[:50]))
- return (best_multiplier, best_adder, best_one_based), best_fit
-
-def keyword_break(message,
- wordlist=keywords,
- metric=norms.euclidean_distance,
- target_counts=normalised_english_counts,
- message_frequency_scaling=norms.normalise):
- """Breaks a keyword substitution cipher using a dictionary and
- frequency analysis
-
- >>> keyword_break(keyword_encipher('this is a test message for the ' \
- 'keyword decipherment', 'elephant', 1), \
- wordlist=['cat', 'elephant', 'kangaroo']) # doctest: +ELLIPSIS
- (('elephant', 1), 0.41643991598441...)
- """
- best_keyword = ''
- best_wrap_alphabet = True
- best_fit = float("inf")
- for wrap_alphabet in range(3):
- for keyword in wordlist:
- plaintext = keyword_decipher(message, keyword, wrap_alphabet)
- counts = message_frequency_scaling(letter_frequencies(plaintext))
- fit = metric(target_counts, counts)
- logger.debug('Keyword break attempt using key {0} (wrap={1}) '
- 'gives fit of {2} and decrypt starting: {3}'.format(
- keyword, wrap_alphabet, fit,
- sanitise(plaintext)[:50]))
- if fit < best_fit:
- best_fit = fit
- best_keyword = keyword
- best_wrap_alphabet = wrap_alphabet
- logger.info('Keyword break best fit with key {0} (wrap={1}) gives fit of '
- '{2} and decrypt starting: {3}'.format(best_keyword,
- best_wrap_alphabet, best_fit, sanitise(
- keyword_decipher(message, best_keyword,
- best_wrap_alphabet))[:50]))
- return (best_keyword, best_wrap_alphabet), best_fit
-
-def keyword_break_mp(message,
- wordlist=keywords,
- metric=norms.euclidean_distance,
- target_counts=normalised_english_counts,
- message_frequency_scaling=norms.normalise,
- chunksize=500):
- """Breaks a keyword substitution cipher using a dictionary and
- frequency analysis
-
- >>> keyword_break_mp(keyword_encipher('this is a test message for the ' \
- 'keyword decipherment', 'elephant', 1), \
- wordlist=['cat', 'elephant', 'kangaroo']) # doctest: +ELLIPSIS
- (('elephant', 1), 0.41643991598441...)
- """
- with Pool() as pool:
- helper_args = [(message, word, wrap, metric, target_counts,
- message_frequency_scaling)
- for word in wordlist for wrap in range(3)]
- # Gotcha: the helper function here needs to be defined at the top level
- # (limitation of Pool.starmap)
- breaks = pool.starmap(keyword_break_worker, helper_args, chunksize)
- return min(breaks, key=lambda k: k[1])
-
-def keyword_break_worker(message, keyword, wrap_alphabet, metric, target_counts,
- message_frequency_scaling):
- plaintext = keyword_decipher(message, keyword, wrap_alphabet)
- counts = message_frequency_scaling(letter_frequencies(plaintext))
- fit = metric(target_counts, counts)
- logger.debug('Keyword break attempt using key {0} (wrap={1}) gives fit of '
- '{2} and decrypt starting: {3}'.format(keyword,
- wrap_alphabet, fit, sanitise(plaintext)[:50]))
- return (keyword, wrap_alphabet), fit
-
-def scytale_break(message,
- metric=norms.euclidean_distance,
- target_counts=normalised_english_bigram_counts,
- message_frequency_scaling=norms.normalise):
- """Breaks a Scytale cipher
-
- >>> scytale_break('tfeulchtrtteehwahsdehneoifeayfsondmwpltmaoalhikotoere' \
- 'dcweatehiplwxsnhooacgorrcrcraotohsgullasenylrendaianeplscdriioto' \
- 'aek') # doctest: +ELLIPSIS
- (6, 0.83453041115025...)
- """
- best_key = 0
- best_fit = float("inf")
- ngram_length = len(next(iter(target_counts.keys())))
- for key in range(1, 20):
- if len(message) % key == 0:
- plaintext = scytale_decipher(message, key)
- counts = message_frequency_scaling(frequencies(
- ngrams(sanitise(plaintext), ngram_length)))
- fit = metric(target_counts, counts)
- logger.debug('Scytale break attempt using key {0} gives fit of '
- '{1} and decrypt starting: {2}'.format(key,
- fit, sanitise(plaintext)[:50]))
- if fit < best_fit:
- best_fit = fit
- best_key = key
- logger.info('Scytale break best fit with key {0} gives fit of {1} and '
- 'decrypt starting: {2}'.format(best_key, best_fit,
- sanitise(scytale_decipher(message, best_key))[:50]))
- return best_key, best_fit
-
-def column_transposition_break(message,
- wordlist=keywords,
- metric=norms.euclidean_distance,
- target_counts=normalised_english_bigram_counts,
- message_frequency_scaling=norms.normalise):
- """Breaks a column transposition cipher using a dictionary and
- n-gram frequency analysis
-
- >>> column_transposition_break(column_transposition_encipher(sanitise( \
- "Turing's homosexuality resulted in a criminal prosecution in 1952, \
- when homosexual acts were still illegal in the United Kingdom. "), \
- 'encipher'), \
- wordlist=['encipher', 'keyword', 'fourteen']) # doctest: +ELLIPSIS
- ('encipher', 0.898128626285...)
- >>> column_transposition_break(column_transposition_encipher(sanitise( \
- "Turing's homosexuality resulted in a criminal prosecution in 1952, " \
- "when homosexual acts were still illegal in the United Kingdom."), \
- 'encipher'), \
- wordlist=['encipher', 'keyword', 'fourteen'], \
- target_counts=normalised_english_trigram_counts) # doctest: +ELLIPSIS
- ('encipher', 1.1958792913127...)
- """
- best_keyword = ''
- best_fit = float("inf")
- ngram_length = len(next(iter(target_counts.keys())))
- for keyword in wordlist:
- if len(message) % len(deduplicate(keyword)) == 0:
- plaintext = column_transposition_decipher(message, keyword)
- counts = message_frequency_scaling(frequencies(
- ngrams(sanitise(plaintext), ngram_length)))
- fit = metric(target_counts, counts)
- logger.debug('Column transposition break attempt using key {0} '
- 'gives fit of {1} and decrypt starting: {2}'.format(
- keyword, fit,
- sanitise(plaintext)[:50]))
- if fit < best_fit:
- best_fit = fit
- best_keyword = keyword
- logger.info('Column transposition break best fit with key {0} gives fit '
- 'of {1} and decrypt starting: {2}'.format(best_keyword,
- best_fit, sanitise(
- column_transposition_decipher(message,
- best_keyword))[:50]))
- return best_keyword, best_fit
-
-
-def column_transposition_break_mp(message,
- wordlist=keywords,
- metric=norms.euclidean_distance,
- target_counts=normalised_english_bigram_counts,
- message_frequency_scaling=norms.normalise,
- chunksize=500):
- """Breaks a column transposition cipher using a dictionary and
- n-gram frequency analysis
-
- >>> column_transposition_break_mp(column_transposition_encipher(sanitise( \
- "Turing's homosexuality resulted in a criminal prosecution in 1952, \
- when homosexual acts were still illegal in the United Kingdom. "), \
- 'encipher'), \
- wordlist=['encipher', 'keyword', 'fourteen']) # doctest: +ELLIPSIS
- ('encipher', 0.898128626285...)
- >>> column_transposition_break_mp(column_transposition_encipher(sanitise( \
- "Turing's homosexuality resulted in a criminal prosecution in 1952, " \
- "when homosexual acts were still illegal in the United Kingdom."), \
- 'encipher'), \
- wordlist=['encipher', 'keyword', 'fourteen'], \
- target_counts=normalised_english_trigram_counts) # doctest: +ELLIPSIS
- ('encipher', 1.1958792913127...)
- """
- ngram_length = len(next(iter(target_counts.keys())))
- with Pool() as pool:
- helper_args = [(message, word, metric, target_counts, ngram_length,
- message_frequency_scaling)
- for word in wordlist]
- # Gotcha: the helper function here needs to be defined at the top level
- # (limitation of Pool.starmap)
- breaks = pool.starmap(column_transposition_break_worker, helper_args, chunksize)
- return min(breaks, key=lambda k: k[1])
-
-def column_transposition_break_worker(message, keyword, metric, target_counts,
- ngram_length, message_frequency_scaling):
- plaintext = column_transposition_decipher(message, keyword)
- counts = message_frequency_scaling(frequencies(
- ngrams(sanitise(plaintext), ngram_length)))
- fit = metric(target_counts, counts)
- logger.debug('Column transposition break attempt using key {0} '
- 'gives fit of {1} and decrypt starting: {2}'.format(
- keyword, fit,
- sanitise(plaintext)[:50]))
- return keyword, fit
-
-def vigenere_keyword_break(message,
- wordlist=keywords,
- metric=norms.euclidean_distance,
- target_counts=normalised_english_counts,
- message_frequency_scaling=norms.normalise):
- """Breaks a vigenere cipher using a dictionary and
- frequency analysis
-
- >>> vigenere_keyword_break(keyword_encipher('this is a test message for the ' \
- 'keyword decipherment', 'elephant', 1), \
- wordlist=['cat', 'elephant', 'kangaroo']) # doctest: +ELLIPSIS
- ('elephant', 0.7166585201707...)
- """
- best_keyword = ''
- best_fit = float("inf")
- for keyword in wordlist:
- plaintext = vigenere_decipher(message, keyword)
- counts = message_frequency_scaling(letter_frequencies(plaintext))
- fit = metric(target_counts, counts)
- logger.debug('Vigenere break attempt using key {0} '
- 'gives fit of {1} and decrypt starting: {2}'.format(
- keyword, fit,
- sanitise(plaintext)[:50]))
- if fit < best_fit:
- best_fit = fit
- best_keyword = keyword
- logger.info('Vigenere break best fit with key {0} gives fit '
- 'of {1} and decrypt starting: {2}'.format(best_keyword,
- best_fit, sanitise(
- vigenere_decipher(message, best_keyword))[:50]))
- return best_keyword, best_fit
-
-def vigenere_keyword_break_mp(message,
- wordlist=keywords,
- metric=norms.euclidean_distance,
- target_counts=normalised_english_counts,
- message_frequency_scaling=norms.normalise,
- chunksize=500):
- """Breaks a vigenere cipher using a dictionary and
- frequency analysis
-
- >>> vigenere_keyword_break_mp(keyword_encipher('this is a test message for the ' \
- 'keyword decipherment', 'elephant', 1), \
- wordlist=['cat', 'elephant', 'kangaroo']) # doctest: +ELLIPSIS
- ('elephant', 0.7166585201707...)
- """
- with Pool() as pool:
- helper_args = [(message, word, metric, target_counts,
- message_frequency_scaling)
- for word in wordlist]
- # Gotcha: the helper function here needs to be defined at the top level
- # (limitation of Pool.starmap)
- breaks = pool.starmap(vigenere_keyword_break_worker, helper_args, chunksize)
- return min(breaks, key=lambda k: k[1])
-
-def vigenere_keyword_break_worker(message, keyword, metric, target_counts,
- message_frequency_scaling):
- plaintext = vigenere_decipher(message, keyword)
- counts = message_frequency_scaling(letter_frequencies(plaintext))
- fit = metric(target_counts, counts)
- logger.debug('Vigenere keyword break attempt using key {0} gives fit of '
- '{1} and decrypt starting: {2}'.format(keyword,
- fit, sanitise(plaintext)[:50]))
- return keyword, fit
-
-
-
if __name__ == "__main__":
import doctest
doctest.testmod()