我尝试的过程是获取密文中每个字母的百分比，与英文频率文本进行比较，并计算密文与参考频率之间的频率差异。接下来，我将两个文件之间的差异标准化（尝试了各种方法；这次常数：50，除数：3；很可能是错误的），并取平均值作为密钥。
主要程序：
attempts = 0
max_attempts = 3
while attempts < max_attempts:
input_file_name = input("Please enter the file you want to analyze: ")
if input_file_name.endswith('.txt') and os.path.exists(input_file_name):
input_text = ManageFile.openFile(input_file_name)
if input_text is None:
print("Error: Unable to read the input file.")
attempts += 1
else:
reference_file_name = input("Please enter the reference frequencies file: ")
if reference_file_name.endswith('.txt') and os.path.exists(reference_file_name):
reference_frequencies = ManageFile.openFile(reference_file_name)
if reference_frequencies is None:
print("Error: Unable to read the reference frequencies file.")
attempts += 1
else:
analyzer = FrequencyAnalyzer(input_text, reference_frequencies)
inferred_cipher_key = analyzer.analyze_text()
print("Inferred Caesar Cipher Key (Number of Shifts):", inferred_cipher_key)
decrypt_file = input("Do you want to decrypt the file? (y/n): ").lower()
if decrypt_file == 'y':
decrypted_text = Caesar(inferred_cipher_key).decrypt(input_text)
print("Decrypted Text:")
print(decrypted_text)
inner_attempts = 0
while inner_attempts < max_attempts:
output_file_name = input("Please enter a output file: ")
if output_file_name.endswith('.txt'):
if os.path.exists(output_file_name):
overwrite = input(f"The file '{output_file_name}' already exists. Do you want to overwrite it? (y/n): ").lower()
if overwrite != 'y':
print("Decryption canceled.")
break # Exit the loop if user doesn't want to overwrite and return to the main menu
else:
print(f"Overwriting the file '{output_file_name}'...")
ManageFile(input_text, inferred_cipher_key).toFile(output_file_name, decrypted_text)
print(f"Decrypted text has been saved to '{output_file_name}'")
break # Exit the loop if a valid output file name is provided
else:
print("Invalid output file name. Please include '.txt' extension.")
inner_attempts += 1
else:
print("Failed to read the file after 3 attempts. Returning to the main menu.")
else:
print("Decryption canceled.")
break
else:
print("Invalid reference frequencies file name or file does not exist. Please include '.txt' extension.")
attempts += 1
else:
print("Invalid input file name or file does not exist. Please include '.txt' extension.")
attempts += 1
if attempts >= max_attempts:
print("Failed to read the file(s) after 3 attempts. Returning to the main menu.")
功能：
class TextAnalyzer:
def __init__(self, text):
self._text = text
self._processed_text = ""
self._all_letters = string.ascii_uppercase
self._cleaned_letters = []
self._cleaned_letters_count = 0
self._individual_letter_counts = {}
self._top_5_letter_counts = []
def _preprocess_text(self):
self._cleaned_letters = list(filter(str.isalpha, self._text.upper()))
self._cleaned_letters_count = len(self._cleaned_letters)
self._individual_letter_counts = collections.Counter(self._cleaned_letters)
self._top_5_letter_counts = self._individual_letter_counts.most_common(5)
self._processed_text = " ".join(self._cleaned_letters)
def analyze_text(self):
self._preprocess_text()
class FrequencyAnalyzer(TextAnalyzer):
def __init__(self, text, frequency_data):
super().__init__(text)
self._frequency_data = {}
lines = frequency_data.split("\\n")
for line in lines:
char, percent = line.strip().split(',')
self._frequency_data[char] = float(percent)
self._letter_percentages = {}
self._inferred_cipher_key = None
def _calculate_letter_percentages(self):
super()._preprocess_text()
total_letters = sum(self._individual_letter_counts.values())
letter_percentages = {
letter: (count / total_letters) * 100 for letter, count in self._individual_letter_counts.items()
}
return letter_percentages
def _normalize_letter_percentages(self, letter_percentages):
normalized_diff = {
letter: (letter_percentages[letter] - self._frequency_data[letter] + 50) % 50 / 3
for letter in letter_percentages
}
return normalized_diff
def _generate_report(self):
letter_percentages = self._calculate_letter_percentages()
normalized_diff = self._normalize_letter_percentages(letter_percentages)
average_normalized_diff = sum(normalized_diff.values()) / len(normalized_diff)
inferred_cipher_key = round(average_normalized_diff)
#print("Inferred Caesar Cipher Key (Number of Shifts):", inferred_cipher_key)
return inferred_cipher_key
# print("Inferred Caesar Cipher Key (Number of Shifts):", inferred_cipher_key)
# print("Final Letter Percentages:")
# for char, percentage in letter_percentages.items():
# print(f"{char}: {percentage:.3f}%")
def analyze_text(self):
inferred_cipher_key = self._generate_report()
return inferred_cipher_key
我有 2 个加密文件和 1 个频率参考文件（百分比）：
英文参考频率文本文件：
A,8.2
B,1.5
C,2.8
D,4.3
E,12.7
F,2.2
G,2.0
H,6.1
I,7.0
J,0.15
K,0.77
L,4.0
M,2.4
N,6.7
O,7.5
P,1.9
Q,0.095
R,6.0
S,6.3
T,9.1
U,2.8
V,0.98
W,2.4
X,0.15
Y,2.0
Z,0.074
当我运行第一个加密文件时，其中包含：
Beqvstm, beqvstm tqbbtm abiz,
pwe Q ewvlmz epib gwc izm.
Cx ijwdm bpm asg aw pqop,
tqsm i lqiuwvl qv bpm asg.
和频率参考文件通过
Please enter the file you want to analyze: Mystery.txt
Please enter the reference frequencies file: englishtext.txt
Inferred Caesar Cipher Key (Number of Shifts): 8
我得到 8，这是正确的，因为新的解密文本是
Twinkle, twinkle little star,
how I wonder what you are.
Up above the sky so high,
like a diamond in the sky.
但是当我尝试第二个加密文本（这是一个正确的句子）时：
Bpm nikba qv bpib kwuxtmf kiam qa ycmabqwvijtm.
应该给
The facts in that complex case is questionable.
作为解密文本， 我应该得到的推断密钥是 8，但得到的是 5。
Please enter the file you want to analyze: facts.txt
Please enter the reference frequencies file: englishtext.txt
Inferred Caesar Cipher Key (Number of Shifts): 5
我什至尝试了其他正确的句子，例如
Wkh shrsoh duh zhdulqj irupdo dwwluh
应该给
The people are wearing formal attire
作为解密文本，
我应该得到的推断密钥是 3，但我得到的是 4。
Please enter the file you want to analyze: attire.txt
Please enter the reference frequencies file: englishtext.txt
Inferred Caesar Cipher Key (Number of Shifts): 4
我使用的方法有什么问题，有更好的方法吗？
显然，您测试的句子没有表现出您期望的较长英语文本的字符分布。您使用的方法对于短文本来说本质上很脆弱。
也许更可靠的方法是收集相邻字母对（或三联体等）的统计信息；顺便说一句，正是这种密码学分析导致安德烈·马尔可夫发明了马尔可夫链。
对于侵入性较小的更改，也许可以尝试您已有的频率分析建议的前三个（或前五个等）旋转键，并对照字典检查哪些看起来最合理 - 或者可能将它们全部显示给用户并让他们选择。