Publication Date

Spring 2015

Degree Type

Master's Project

Degree Name

Master of Science (MS)


Computer Science

First Advisor

Mark Stamp

Second Advisor

Richard Low

Third Advisor

Thomas Austin


Classic Ciphers Hidden Markov Models


Cryptanalysis is the study of identifying weaknesses in the implementation of cryptographic algorithms. This process would improve the complexity of such algo- rithms, making the system secure.

In this research, we apply Hidden Markov Models (HMMs) to classic cryptanaly- sis problems. We show that with sufficient ciphertext, an HMM can be used to break a simple substitution cipher. We also show that when limited ciphertext is avail- able, using multiple random restarts for the HMM increases our chance of successful decryption.