most citedLongitudinal Study of the Prevalence of Malware Evasive Techniques

8 citations · 8 across the 2 of their papers we have counts for

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cs.CR2023

Decoding the Secrets of Machine Learning in Malware Classification: A Deep Dive into Datasets, Feature Extraction, and Model Performance

Savino Dambra, Yufei Han, Simone Aonzo +5

Many studies have proposed machine-learning (ML) models for malware detection and classification, reporting an almost-perfect performance. However, they assemble ground-truth in di…

cs.CR2021★ 8 cited

Longitudinal Study of the Prevalence of Malware Evasive Techniques

Lorenzo Maffia, Dario Nisi, Platon Kotzias +3

By their very nature, malware samples employ a variety of techniques to conceal their malicious behavior and hide it from analysis tools. To mitigate the problem, a large number of…