The method to decrypt the information using probability leads to a more thorough job, because you have to know the percentage of each of the letters of the language that is being analyzed here is Spanish. You can consider not only the probabilities of the letters also syllables, set of three, four letters and even words. Then you have this thing to do is make comparisons of the frequencies of cipher text and the frequencies of the language to begin to replace by a correspondence. And ¯nally passing a scanner and ¯nd the decrypted text.
Cryptography is the science that alters the linguistic representations of a message
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Decryption is the reverse process to recover the plaintext from the ciphertext
and key. Cryptographic protocol speci¯es the details of how to use algorithms
and keys (and other primitive operations) to achieve the desired e®ect. The set
of protocols, encryption algorithms, key management processes and actions of
the users, which together constitute a cryptosystem, which is what the end user
works and interacts. In this work, we must ¯rst have a ciphertext which must
meet certain requirements, such a text should be bijective so that each element
of the domain carries a single element of the condominium. In addition we must
also take account of the rules of Kerckho® [
Is required to decrypt text using the odds as to how often they used certain
letters in the alphabet, for this work only considered the Spanish language [
The frequencies of Spanish, which were used for this study were: 1. Frequency triglyphs 2. Frequency of digraphs 3. Most common words 4. Frequency of letters at the beginning of words 5. Frequency of letters in Spanish 6. Frequency Words 2.2
The letter frequency statistics may vary from one to another depending on the corpus author has chosen to develop them. Usually di®erences when the corpus is literary or consists of texts of di®erent origins. Table 1 shows the frequency of each of the Spanish alphabet with their respective percentage. 2.3
The vowels make up about 46.38% of the text. The high frequency letters account
for 67.56% of the text. Mid-frequency points accounting for 25% of the text [
Next, table 3 shows the frequencies of the 4-letter words. The size of the corpus is 60,115 letters. The frequencies are absolute. The digraphs are read by row and column in that order. Below in table 4 shows the union digraphs are letters from letters. The ciphertext is used as said it had to be bijective and have Kerckho® rules and the decrypted text shown in Figure 1. Four-letter words Distribution of letters in literary texts Word Frequency E - 16,78% R - 4,94% Y - 1,54% J - 0,30% PARA 67 A - 11,96% U - 4,80% Q - 1,53% COMO 36 O - 8,69% I - 4,15% B - 0,92% AYER 25 L - 8,37% T - 3,31% H - 0,89% ESTE 23 S - 7,88% C - 2,92% G - 0,73% PERO 18 N - 7,01% P - 2,77% F - 0,52% ESTA 17 D - 6,87% M - 2,12% V - 0,39% AOS 14 TODO 11 SIDO 11 SOLO 10 We conclude that this method of decryption is good however would have to tweak a little more due to it depends on the text we have and how much text to decrypt was also observed that only decrypts an encrypted bijective. In this work, as seen in the results of Figure 1, which apply various processes, ¯rst see the probability of the lyrics in Spanish that are more frequent, then seen with the syllables that are more frequent in Spanish, and then with the last word and you miss the information, text analyzer, as shown in Figure 1 a large percentage of the information is decoded, but as mentioned in the top, this will depend have that much information to process it.