Monoalphabetic Substitution -Cryptography [已关闭]

问：

我需要帮助完成这个练习：

以下文本已通过字母替换进行编码 密码。这意味着，密文字母表包含相同的 字母作为明文字母表，但字母的顺序有 被打乱了。这是一个单字母替换密码。

LYMBXJXKBBKBJPJJBBKBJPZPHYXNJKGOLOGPIEYHKBIXJSOEPVJBPMBXJEPONKBIEJGJOEATPYOXUOBAJPTJLKJDXGYLOEPKLKAKODKBPJDDKIJBAJXOPOGAKJBAJAYVSMPJEGAKJBAJOSSDKJXVOPTJVOPKAGOBXEYFYPKAGLMEPTJEVYEJXNJVOKBPOKBGODOEIJBJPHYENYLKBXMGPEZSOEPBJEGPTEYMITPTJOHOEXHKBBKBINJHYENSEYIEOVVJOBXPTEYMITYMEEJGJOEATAYDDOFYEOPKYBGPTJXJSOEPVJBPSEYUKXJGJXMAOPKYBPTEYMITYBJFOATJDYEGSEYIEOVVJOBXPHYVOGPJEGSEYIEOVVJGEJGJOEATOPPTJXJSOEPVJBPYLXOPOGAKJBAJOBXNBYHDJXIJJBIKBJJEKBIGSOBGPTJXKGAKSDKBJGOBXKBPJELOAJGYLOEPKLKAKODKBPJDDKIJBAJXOPOGAKJBAJAYVSMPJEGAKJBAJOBXOSSDKJXVOPTJVOPKAGHJXJUJDYSBJHPYYDGOBXVJPTYXYDYIKJGPYOXUOBAJPTJGJLKJDXGOPPTJGOVJPKVJHJAYDDOFYEOPJHKPTOHKXJEOBIJYLKBGPKPMPJGFYPTHKPTKBOBXYMPGKXJYLVOOGPEKATPMBKUJEGKPZOBXHYENYBXKUJEGJOSSDKAOPKYBGKBADMXKBIKBPTJLKJDXGYLTJODPTOBXVJXKAKBJDYIKGPKAGFKYDYIZOEPSTZGKAGAZFJEGJAMEKPZBJMEYGAKJBAJOBXJXMAOPKYB

文本是用英文写的。分析每个字母的频率 并尝试重建密文字母表以及 明文

我尝试了不同的频率分析方法，但我的字母表是错误的，因此文本是错误的。 在我完成频率的分析比较后，我期待看到这个字母表的替换：CNJLRBSWGEIFUKATZQPHVMXDOY for ABCDEFGHIJKLMNOPQSTUVWXYZ

我尝试过在 python 中使用不同的编码，但无论我做什么，一切似乎都是错误的

这是我尝试过的 python 代码：

from collections import Counter

文本=”LYMBXJXKBBKBJPJJBBKBJPZPHYXNJKGOLOGPIEYHKBIXJSOEPVJBPMBXJEPONKBIEJGJOEATPYOXUOBAJPTJLKJDXGYLOEPKLKAKODKBPJDDKIJBAJXOPOGAKJBAJAYVSMPJEGAKJBAJOSSDKJXVOPTJVOPKAGOBXEYFYPKAGLMEPTJEVYEJXNJVOKBPOKBGODOEIJBJPHYENYLKBXMGPEZSOEPBJEGPTEYMITPTJOHOEXHKBBKBINJHYENSEYIEOVVJOBXPTEYMITYMEEJGJOEATAYDDOFYEOPKYBGPTJXJSOEPVJBPSEYUKXJGJXMAOPKYBPTEYMITYBJFOATJDYEGSEYIEOVVJOBXPHYVOGPJEGSEYIEOVVJGEJGJOEATOPPTJXJSOEPVJBPYLXOPOGAKJBAJOBXNBYHDJXIJJBIKBJJEKBIGSOBGPTJXKGAKSDKBJGOBXKBPJELOAJGYLOEPKLKAKODKBPJDDKIJBAJXOPOGAKJBAJAYVSMPJEGAKJBAJOBXOSSDKJXVOPTJVOPKAGHJXJUJDYSBJHPYYDGOBXVJPTYXYDYIKJGPYOXUOBAJPTJGJLKJDXGOPPTJGOVJPKVJHJAYDDOFYEOPJHKPTOHKXJEOBIJYLKBGPKPMPJGFYPTHKPTKBOBXYMPGKXJYLVOOGPEKATPMBKUJEGKPZOBXHYENYBXKUJEGJOSSDKAOPKYBGKBADMXKBIKBPTJLKJDXGYLTJODPTOBXVJXKAKBJDYIKGPKAGFKYDYIZOEPSTZGKAGAZFJEGJAMEKPZBJMEYGAKJBAJOBXJXMAOPKYB”

letter_occurrences = {letter: text.count(letter) for letter in 
set(text)}

 # Convert to dictionary
 letter_occurrences_dict = {letter: count for letter, count in 
 letter_occurrences.items()}

# Print the dictionary
print(f"{sorted(letter_occurrences_dict.items(), key=lambda x: x[1], 
reverse=True)}")    
def calculate_probabilities(text):
text =  text
letter_occurrences = Counter(text)
total_letters = sum(letter_occurrences.values())
print (total_letters)

probabilities = {letter: count / total_letters for letter, count in letter_occurrences.items()}

return probabilities

文本=”LYMBXJXKBBKBJPJJBBKBJPZPHYXNJKGOLOGPIEYHKBIXJSOEPVJBPMBXJEPONKBIEJGJOEATPYOXUOBAJPTJLKJDXGYLOEPKLKAKODKBPJDDKIJBAJXOPOGAKJBAJAYVSMPJEGAKJBAJOSSDKJXVOPTJVOPKAGOBXEYFYPKAGLMEPTJEVYEJXNJVOKBPOKBGODOEIJBJPHYENYLKBXMGPEZSOEPBJEGPTEYMITPTJOHOEXHKBBKBINJHYENSEYIEOVVJOBXPTEYMITYMEEJGJOEATAYDDOFYEOPKYBGPTJXJSOEPVJBPSEYUKXJGJXMAOPKYBPTEYMITYBJFOATJDYEGSEYIEOVVJOBXPHYVOGPJEGSEYIEOVVJGEJGJOEATOPPTJXJSOEPVJBPYLXOPOGAKJBAJOBXNBYHDJXIJJBIKBJJEKBIGSOBGPTJXKGAKSDKBJGOBXKBPJELOAJGYLOEPKLKAKODKBPJDDKIJBAJXOPOGAKJBAJAYVSMPJEGAKJBAJOBXOSSDKJXVOPTJVOPKAGHJXJUJDYSBJHPYYDGOBXVJPTYXYDYIKJGPYOXUOBAJPTJGJLKJDXGOPPTJGOVJPKVJHJAYDDOFYEOPJHKPTOHKXJEOBIJYLKBGPKPMPJGFYPTHKPTKBOBXYMPGKXJYLVOOGPEKATPMBKUJEGKPZOBXHYENYBXKUJEGJOSSDKAOPKYBGKBADMXKBIKBPTJLKJDXGYLTJODPTOBXVJXKAKBJDYIKGPKAGFKYDYIZOEPSTZGKAGAZFJEGJAMEKPZBJMEYGAKJBAJOBXJXMAOPKYB”

letter_probabilities = calculate_probabilities(text)

for letter, probability in letter_probabilities.items():
print(f" '{letter}':{probability:.4f}")
def calculate_ngram(text, n):
ngrams = [text[i:i+n] for i in range(len(text)-n+1)]
ngram_occurrences = Counter(ngrams)

return ngram_occurrences

文本 =“LYMBXJXKBBKBJPJJBBKBJPZPHYXNJKGOLOGPIEYHKBIXJSOEPVJBPMBXJEPONKBIEJGJOEATPYOXUOBAJPTJLKJDXGYLOEPKLKAKODKBPJDDKIJBAJXOPOGAKJBAJAYVSMPJEGAKJBAJOSSDKJXVOPTJVOPKAGOBXEYFYPKAGLMEPTJEVYEJXNJVOKBPOKBGODOEIJBJPHYENYLKBXMGPEZSOEPBJEGPTEYMITPTJOHOEXHKBBKBINJHYEN 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”

bigram_probabilities = calculate_ngram(text, 2)
trigram_probabilities = calculate_ngram(text, 3)

# Print the results

for bigram, probability in sorted(bigram_probabilities.items(), 
key=lambda x: x[1], reverse=True):
print(f"{bigram} :{probability:.4f}")

trigram_probabilities = calculate_ngram(text, 3)

# Sort trigram probabilities in descending order
sorted_trigram_probabilities = sorted(trigram_probabilities.items(), 
key=lambda x: x[1], reverse=True)

# Print sorted trigram probabilities
for trigram, probability in sorted_trigram_probabilities:
print(f"Trigram: '{trigram}', Probability: {probability}")