Master of Science (MS)
Fabio Di Troia
Previous research has applied classic cryptanalytic techniques to the malware detection problem. Speci cally, scores based on simple substitution cipher cryptanal- ysis and various generalizations have been considered. In this research, we analyze two new malware scoring techniques based on classic cryptanalysis. Our rst ap- proach relies on the Index of Coincidence, which is used, for example, to determine the length of the keyword in a Vigenère ciphertext. We also consider a score based on a more complete cryptanalysis of a Vigenère cipher. We nd that the Vigenère score is competitive with previous statistical-based malware scores.
Deshmukh, Suchita, "Vigenère Score for Malware Detection" (2016). Master's Projects. 487.