Master of Science (MS)
Fabio Di Troia
Java Malware Code Obfuscation Signature Statistical Detection
In this research, we consider the problem of detecting malicious Java applets, based on static analysis. In general, dynamic analysis is more informative, but static analysis is more efficient, and hence more practical. Consequently, static analysis is preferred, provided we can obtain results comparable to those obtained using dynamic analysis. We conducted experiments with the machine learning technique, Hidden Markov Model (HMM). We show that in some cases a static technique can detect malicious Java applets with greater accuracy than previously published research that relied on dynamic analysis.
Ganesh, Nikitha, "Static Analysis of Malicious Java Applets" (2015). Master's Projects. 390.