Cryptanalysis of Classic Ciphers Using Hidden Markov Models

Vobbilisetty, Rohit

doi:10.31979/etd.qxu5-d8pk

Cited by 1 publication

(3 citation statements)

References 7 publications

(22 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…• We use randomly generated seed values to initialize the matrices π and B [19] • We compute the random plugboard permutations…”

Section: Overview Of the Algorithmmentioning

confidence: 99%

“…• The decryption key can be obtained from matrix B, which contains the emission probability for the observation symbols (cipher text) and the plaintext symbols. We can choose the most probable internal state (plaintext symbol) for each of the cipher text symbols [19]. This is explained in detail in Section 4.1.1.…”

Section: Overview Of the Algorithmmentioning

confidence: 99%

“…observation symbols (1 to 4) [19]. This contains the final emission probabilities after the training.…”

Section: Computation Of the Decryption Keymentioning

confidence: 99%

See 2 more Smart Citations

Cryptanalysis of the Purple Cipher using Random Restarts

Shikhare

View full text Add to dashboard Cite

Cryptanalysis of the Purple Cipher using Random Restarts by Aparna Shikhare Cryptanalysis is the process of trying to analyze ciphers, cipher text, and crypto systems, which may exploit any loopholes or weaknesses in the systems, leading us to an understanding of the key used to encrypt the data. This project uses Expectation Maximization (EM) approach using numerous restarts to attack decipherment problems such as the Purple Cipher. In this research, we perform cryptanalysis of the Purple cipher using genetic algorithms and hidden Markov models (HMM). If the Purple cipher has a fixed plugboard, we show that genetic algorithms are successful in retrieving the plaintext from cipher text with high accuracy. On the other hand, if the cipher has a plugboard that is not fixed, we can decrypt the cipher text with increasing accuracy given an increase in population size and restarts. We performed the cryptanalysis of PseudoPurple, which is less complex but more powerful than Purple using HMMs. Though we could not decrypt cipher text produced by PseudoPurple with good accuracy, there is an increase in accuracy of the decrypted plaintext with an increase in the number of restarts.

show abstract

“…• We use randomly generated seed values to initialize the matrices π and B [19] • We compute the random plugboard permutations…”

Section: Overview Of the Algorithmmentioning

confidence: 99%

Section: Overview Of the Algorithmmentioning

confidence: 99%