Title :
Malware behavior image for malware variant identification
Author :
Mohd Shaid, Syed Zainudeen ; Maarof, Mohd Aizaini
Author_Institution :
Fac. of Comput., Univ. Teknol. Malaysia, Skudai, Malaysia
Abstract :
Several methods have been devised by researchers to facilitate malware analysis and one of them is through malware visualization. Malware visualization is a field that focuses on representing malware features in a form of visual cues that could be used to convey more information about a particular malware. There has been works in malware visualization but unfortunately, there seems to be a lack of focus in visualizing malware behavior. In this paper, we highlight our findings in visualizing malware behavior and its potential benefit for malware classification. Our research shows that malware behavior visualization can be used as a way to identify malware variants with high accuracy.
Keywords :
data visualisation; image classification; image representation; invasive software; malware analysis; malware behavior image; malware behavior visualization; malware features representation; malware image classification; malware variant identification; visual cues; Accuracy; Data visualization; Image color analysis; Malware; Monitoring; Software; Visualization; API Call; Malware; Malware Behavior Visualization; Malware Image; Malware Variant Identification;
Conference_Titel :
Biometrics and Security Technologies (ISBAST), 2014 International Symposium on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4799-6443-7
DOI :
10.1109/ISBAST.2014.7013128