| Title | Malware Family Fingerprinting Through Behavioral Analysis |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Walker, Aaron, Sengupta, Shamik |
| Conference Name | 2020 IEEE International Conference on Intelligence and Security Informatics (ISI) |
| Keywords | behavior analysis, Conferences, dynamic analysis, Fingerprint recognition, Fingerprinting, Human Behavior, Informatics, machine learning, Malware, malware analysis, malware detection, Malware Signature, Predictive Metrics, privacy, pubcrawl, Resiliency, security |
| Abstract | Signature-based malware detection is not always effective at detecting polymorphic variants of known malware. Malware signatures are devised to counter known threats, which also limits efficacy against new forms of malware. However, existing signatures do present the ability to classify malware based upon known malicious behavior which occurs on a victim computer. In this paper we present a method of classifying malware by family type through behavioral analysis, where the frequency of system function calls is used to fingerprint the actions of specific malware families. This in turn allows us to demonstrate a machine learning classifier which is capable of distinguishing malware by family affiliation with high accuracy. |
| DOI | 10.1109/ISI49825.2020.9280529 |
| Citation Key | walker_malware_2020 |
Malware Family Fingerprinting Through Behavioral Analysis