From ba1b36c3d4e8bb462bde276b27a3aca9e7b6a197 Mon Sep 17 00:00:00 2001 From: Neil Smith Date: Mon, 27 Nov 2017 13:14:23 +0000 Subject: [PATCH] Got hillclimbing and simulated annealing searches working --- cipherbreak.py | 178 +++++++++++++++++++++++++++++++++++++-------- language_models.py | 30 +++----- 2 files changed, 158 insertions(+), 50 deletions(-) diff --git a/cipherbreak.py b/cipherbreak.py index e3c1e5f..a70e835 100644 --- a/cipherbreak.py +++ b/cipherbreak.py @@ -221,35 +221,110 @@ def keyword_break_worker(message, keyword, wrap_alphabet, fitness): wrap_alphabet, fit, sanitise(plaintext)[:50])) return (keyword, wrap_alphabet), fit -def monoalphabetic_break_hillclimbing(message, max_iterations=10000000, - alphabet=None, fitness=Pletters): - ciphertext = unaccent(message).lower() - if not alphabet: - alphabet = list(string.ascii_lowercase) - random.shuffle(alphabet) - alphabet = cat(alphabet) - return monoalphabetic_break_hillclimbing_worker(ciphertext, alphabet, - max_iterations, fitness) - -def monoalphabetic_break_hillclimbing_mp(message, workers=10, - max_iterations = 10000000, alphabet=None, fitness=Pletters, chunksize=1): +# def monoalphabetic_break_hillclimbing(message, max_iterations=10000000, +# alphabet=None, fitness=Pletters): +# ciphertext = unaccent(message).lower() +# if not alphabet: +# alphabet = list(string.ascii_lowercase) +# random.shuffle(alphabet) +# alphabet = cat(alphabet) +# return monoalphabetic_break_hillclimbing_worker(ciphertext, alphabet, +# max_iterations, fitness) + +# def monoalphabetic_break_hillclimbing_mp(message, workers=10, +# max_iterations = 10000000, alphabet=None, fitness=Pletters, chunksize=1): +# worker_args = [] +# ciphertext = unaccent(message).lower() +# for i in range(workers): +# if alphabet: +# this_alphabet = alphabet +# else: +# this_alphabet = list(string.ascii_lowercase) +# random.shuffle(this_alphabet) +# this_alphabet = cat(this_alphabet) +# worker_args.append((ciphertext, this_alphabet, max_iterations, fitness)) +# with Pool() as pool: +# breaks = pool.starmap(monoalphabetic_break_hillclimbing_worker, +# worker_args, chunksize) +# return max(breaks, key=lambda k: k[1]) + +# def monoalphabetic_break_hillclimbing_worker(message, alphabet, +# max_iterations, fitness): +# def swap(letters, i, j): +# if i > j: +# i, j = j, i +# if i == j: +# return letters +# else: +# return (letters[:i] + letters[j] + letters[i+1:j] + letters[i] + +# letters[j+1:]) +# best_alphabet = alphabet +# best_fitness = float('-inf') +# for i in range(max_iterations): +# alphabet = swap(best_alphabet, random.randrange(26), random.randrange(26)) +# cipher_translation = ''.maketrans(string.ascii_lowercase, alphabet) +# plaintext = message.translate(cipher_translation) +# if fitness(plaintext) > best_fitness: +# best_fitness = fitness(plaintext) +# best_alphabet = alphabet +# print(i, best_alphabet, best_fitness, plaintext[:50]) +# return best_alphabet, best_fitness + + +def monoalphabetic_break_hillclimbing(message, + max_iterations=20000, + plain_alphabet=None, + cipher_alphabet=None, + fitness=Pletters, chunksize=1): + return simulated_annealing_break(message, + workers=1, + initial_temperature=0, + max_iterations=max_iterations, + plain_alphabet=plain_alphabet, + cipher_alphabet=cipher_alphabet, + fitness=fitness, chunksize=chunksize) + + +def monoalphabetic_break_hillclimbing_mp(message, + workers=10, + max_iterations=20000, + plain_alphabet=None, + cipher_alphabet=None, + fitness=Pletters, chunksize=1): + return simulated_annealing_break(message, + workers=workers, + initial_temperature=0, + max_iterations=max_iterations, + plain_alphabet=plain_alphabet, + cipher_alphabet=cipher_alphabet, + fitness=fitness, chunksize=chunksize) + + +def simulated_annealing_break(message, workers=10, + initial_temperature=200, + max_iterations=20000, + plain_alphabet=None, + cipher_alphabet=None, + fitness=Pletters, chunksize=1): worker_args = [] - ciphertext = unaccent(message).lower() + ciphertext = sanitise(message) for i in range(workers): - if alphabet: - this_alphabet = alphabet - else: - this_alphabet = list(string.ascii_lowercase) - random.shuffle(this_alphabet) - this_alphabet = cat(this_alphabet) - worker_args.append((ciphertext, this_alphabet, max_iterations, fitness)) + if not plain_alphabet: + plain_alphabet = string.ascii_lowercase + if not cipher_alphabet: + cipher_alphabet = list(string.ascii_lowercase) + random.shuffle(cipher_alphabet) + cipher_alphabet = cat(cipher_alphabet) + worker_args.append((ciphertext, plain_alphabet, cipher_alphabet, + initial_temperature, max_iterations, fitness)) with Pool() as pool: - breaks = pool.starmap(monoalphabetic_break_hillclimbing_worker, + breaks = pool.starmap(simulated_annealing_break_worker, worker_args, chunksize) return max(breaks, key=lambda k: k[1]) -def monoalphabetic_break_hillclimbing_worker(message, alphabet, - max_iterations, fitness): + +def simulated_annealing_break_worker(message, plain_alphabet, cipher_alphabet, + t0, max_iterations, fitness): def swap(letters, i, j): if i > j: i, j = j, i @@ -258,17 +333,56 @@ def monoalphabetic_break_hillclimbing_worker(message, alphabet, else: return (letters[:i] + letters[j] + letters[i+1:j] + letters[i] + letters[j+1:]) - best_alphabet = alphabet - best_fitness = float('-inf') + + temperature = t0 + + dt = t0 / (0.9 * max_iterations) + + current_alphabet = cipher_alphabet + alphabet = current_alphabet + cipher_translation = ''.maketrans(current_alphabet, plain_alphabet) + plaintext = message.translate(cipher_translation) + current_fitness = fitness(plaintext) + + best_alphabet = current_alphabet + best_fitness = current_fitness + best_plaintext = plaintext + + # print('starting for', max_iterations) for i in range(max_iterations): - alphabet = swap(alphabet, random.randrange(26), random.randrange(26)) - cipher_translation = ''.maketrans(string.ascii_lowercase, alphabet) + swap_a = random.randrange(26) + swap_b = (swap_a + int(random.gauss(0, 4))) % 26 + alphabet = swap(current_alphabet, swap_a, swap_b) + cipher_translation = ''.maketrans(alphabet, plain_alphabet) plaintext = message.translate(cipher_translation) - if fitness(plaintext) > best_fitness: - best_fitness = fitness(plaintext) - best_alphabet = alphabet - print(i, best_alphabet, best_fitness, plaintext) - return best_alphabet, best_fitness + new_fitness = fitness(plaintext) + try: + sa_chance = math.exp((new_fitness - current_fitness) / temperature) + except (OverflowError, ZeroDivisionError): + # print('exception triggered: new_fit {}, current_fit {}, temp {}'.format(new_fitness, current_fitness, temperature)) + sa_chance = 0 + if (new_fitness > current_fitness or random.random() < sa_chance): + # logger.debug('Simulated annealing: iteration {}, temperature {}, ' + # 'current alphabet {}, current_fitness {}, ' + # 'best_plaintext {}'.format(i, temperature, current_alphabet, + # current_fitness, best_plaintext[:50])) + + # logger.debug('new_fit {}, current_fit {}, temp {}, sa_chance {}'.format(new_fitness, current_fitness, temperature, sa_chance)) + current_fitness = new_fitness + current_alphabet = alphabet + + if current_fitness > best_fitness: + best_alphabet = current_alphabet + best_fitness = current_fitness + best_plaintext = plaintext + if i % 500 == 0: + logger.debug('Simulated annealing: iteration {}, temperature {}, ' + 'current alphabet {}, current_fitness {}, ' + 'best_plaintext {}'.format(i, temperature, current_alphabet, + current_fitness, best_plaintext[:50])) + temperature = max(temperature - dt, 0.001) + + return best_alphabet, best_fitness # current_alphabet, current_fitness def vigenere_keyword_break_mp(message, wordlist=keywords, fitness=Pletters, diff --git a/language_models.py b/language_models.py index 0fa6e85..da5d2d0 100644 --- a/language_models.py +++ b/language_models.py @@ -76,20 +76,20 @@ with open(os.path.join(os.path.dirname(os.path.realpath(__file__)), 'words.txt') def weighted_choice(d): - """Generate random item from a dictionary of item counts - """ - target = random.uniform(0, sum(d.values())) - cuml = 0.0 - for (l, p) in d.items(): - cuml += p - if cuml > target: - return l - return None + """Generate random item from a dictionary of item counts + """ + target = random.uniform(0, sum(d.values())) + cuml = 0.0 + for (l, p) in d.items(): + cuml += p + if cuml > target: + return l + return None def random_english_letter(): - """Generate a random letter based on English letter counts - """ - return weighted_choice(normalised_english_counts) + """Generate a random letter based on English letter counts + """ + return weighted_choice(normalised_english_counts) def ngrams(text, n): @@ -144,12 +144,6 @@ def Pbigrams(letters): """ return sum(P2l[p] for p in ngrams(letters, 2)) -def Pbigrams(letters): - """The Naive Bayes log probability of the bigrams formed from a sequence - of letters. - """ - return sum(P2l[p] for p in ngrams(letters, 2)) - def Ptrigrams(letters): """The Naive Bayes log probability of the trigrams formed from a sequence of letters. -- 2.34.1