In recent years, researchers have relied heavily on labels provided by antivirus companies in establishing ground truth for applications and algorithms of malware detection, classification, and clustering. Furthermore, companies use those labels for guiding their mitigation and disinfection efforts. However, ironically, there is no prior systematic work that validates the performance of antivirus vendors, the reliability of those labels (or even detections), or how they affect the said applications. Equipped with malware samples of several malware families that are manually inspected and labeled, we pose the following questions: How do different antivirus scans perform relatively? How correct are the labels given by those scans? How consistent are AV scans among each other? Our answers to these questions reveal alarming results about the correctness, completeness, coverage, and consistency of the labels utilized by much existing research. We invite the research community to challenge the assumption of relying on antivirus scans and labels as a ground truth for evaluating malware analysis and classification techniques. © 2014 Springer International Publishing Switzerland.
CITATION STYLE
Mohaisen, A., Alrawi, O., Larson, M., & McPherson, D. (2014). Towards a methodical evaluation of antivirus scans and labels “if you’re not confused, you’re not paying attention.” In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8267 LNCS, pp. 231–241). Springer Verlag. https://doi.org/10.1007/978-3-319-05149-9_15
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