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]
c = (a * b) % 26
modular_division_table[b][c] = a
+def letters(text):
+ """Remove all non-alphabetic characters from a text
+ >>> letters('The Quick')
+ 'TheQuick'
+ >>> letters('The Quick BROWN fox jumped! over... the (9lazy) DOG')
+ 'TheQuickBROWNfoxjumpedoverthelazyDOG'
+ """
+ return ''.join([c for c in text if c in string.ascii_letters])
def sanitise(text):
"""Remove all non-alphabetic characters and convert the text to lowercase
>>> sanitise('The Quick BROWN fox jumped! over... the (9lazy) DOG')
'thequickbrownfoxjumpedoverthelazydog'
"""
- sanitised = [c.lower() for c in text if c in string.ascii_letters]
- return ''.join(sanitised)
+ # sanitised = [c.lower() for c in text if c in string.ascii_letters]
+ # return ''.join(sanitised)
+ return letters(text).lower()
def ngrams(text, n):
"""Returns all n-grams of a text
('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)]
- """
- counts = collections.defaultdict(int)
- for c in text:
- counts[c] += 1
- return counts
+ >>> 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):
def transpositions_of(keyword):
- """
+ """Finds the transpostions given by a keyword. For instance, the keyword
+ 'clever' rearranges to 'celrv', so the first column (0) stays first, the
+ second column (1) moves to third, the third column (2) moves to second,
+ and so on.
+
>>> transpositions_of('clever')
[0, 2, 1, 4, 3]
"""
transpositions = [key.index(l) for l in sorted(key)]
return transpositions
-def column_transposition_encipher(message, keyword):
- """
+def column_transposition_encipher(message, keyword, fillvalue=' '):
+ """Enciphers using the column transposition cipher.
+ Message is padded to allow all rows to be the same length.
+
>>> column_transposition_encipher('hellothere', 'clever')
'hleolteher'
+ >>> column_transposition_encipher('hellothere', 'cleverly', fillvalue='!')
+ 'hleolthre!e!'
"""
- return column_transposition_worker(message, keyword, True)
+ return column_transposition_worker(message, keyword, encipher=True,
+ fillvalue=fillvalue)
+
+def column_transposition_decipher(message, keyword, fillvalue=' '):
+ """Deciphers using the column transposition cipher.
+ Message is padded to allow all rows to be the same length.
-def column_transposition_decipher(message, keyword):
- """
>>> column_transposition_decipher('hleolteher', 'clever')
'hellothere'
+ >>> column_transposition_decipher('hleolthre!e!', 'cleverly', fillvalue='?')
+ 'hellothere!!'
"""
- return column_transposition_worker(message, keyword, False)
+ return column_transposition_worker(message, keyword, encipher=False,
+ fillvalue=fillvalue)
+
+def column_transposition_worker(message, keyword,
+ encipher=True, fillvalue=' '):
+ """Does the actual work of the column transposition cipher.
+ Message is padded with spaces to allow all rows to be the same length.
-def column_transposition_worker(message, keyword, encipher=True):
- """
>>> column_transposition_worker('hellothere', 'clever')
'hleolteher'
- >>> column_transposition_worker('hellothere', 'clever', True)
+ >>> column_transposition_worker('hellothere', 'clever', encipher=True)
'hleolteher'
- >>> column_transposition_worker('hleolteher', 'clever', False)
+ >>> column_transposition_worker('hleolteher', 'clever', encipher=False)
'hellothere'
"""
transpositions = transpositions_of(keyword)
- columns = every_nth(message, len(transpositions), fillvalue=' ')
+ columns = every_nth(message, len(transpositions), fillvalue=fillvalue)
if encipher:
transposed_columns = transpose(columns, transpositions)
else:
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
+
+
if __name__ == "__main__":
import doctest
projects / cipher-tools.git / blobdiff