Static Analysis of Malicious Java Applets

Nikitha Ganesh, Fabio Di Troia, Visaggio Aaron Corrado, Thomas H. Austin, Mark Stamp
2016 Proceedings of the 2016 ACM on International Workshop on Security And Privacy Analytics - IWSPA '16  
Static Analysis of Malicious Java Applets by Nikitha Ganesh 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
more » ... 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. ACKNOWLEDGMENTS I would like to thank my project advisor Dr. Mark Stamp for his continuous guidance and for also believing in me. Without his guidance, mentoring and support, this project would not have been completed. Also I would want to thank him for his patience throughout the process.
doi:10.1145/2875475.2875477 dblp:conf/codaspy/GaneshTCAS16 fatcat:ws4kia4cejg77jet25c7bimyii