Malware Detection Using Dynamic Birthmarks
| Title | Malware Detection Using Dynamic Birthmarks |
| Publication Type | Conference Paper |
| Year of Publication | 2016 |
| Authors | Vemparala, Swapna, Di Troia, Fabio, Corrado, Visaggio Aaron, Austin, Thomas H., Stamo, Mark |
| Conference Name | Proceedings of the 2016 ACM on International Workshop on Security And Privacy Analytics |
| Publisher | ACM |
| Conference Location | New York, NY, USA |
| ISBN Number | 978-1-4503-4077-9 |
| Keywords | dynamic analysis, Hidden Markov models, Human Behavior, Malware, malware classification, Metrics, privacy, profile hidden markov models, pubcrawl, Resiliency, static analysis |
| Abstract | In this paper, we compare the effectiveness of Hidden Markov Models (HMMs) with that of Profile Hidden Markov Models (PHMMs), where both are trained on sequences of API calls. We compare our results to static analysis using HMMs trained on sequences of opcodes, and show that dynamic analysis achieves significantly stronger results in many cases. Furthermore, in comparing our two dynamic analysis approaches, we find that using PHMMs consistently outperforms our technique based on HMMs. |
| URL | http://doi.acm.org/10.1145/2875475.2875476 |
| DOI | 10.1145/2875475.2875476 |
| Citation Key | vemparala_malware_2016 |