Publication Date

Spring 2015

Degree Type

Master's Project

Degree Name

Master of Science (MS)


Computer Science

First Advisor

Thomas Austin

Second Advisor

Chris Pollett

Third Advisor

Fabio Di Troia


With the increasing use of the Internet, malicious software has more frequently been designed to take control of users computers for illicit purposes. Cybercriminals are putting a lot of efforts to make malware difficult to detect. In this study, we demonstrate how the metamorphic JavaScript malware can effect a victim’s machine using a malicious or compromised Firefox add-on. Following the same methodology, we develop another add-on with malware static detection technique to detect metamorphic JavaScript malware.