Transformer-based malware detection using process resource utilization metrics
Malware detection has long relied on signature-based methods limited in detecting zero-day malware attacks. Although efficient, these approaches are vulnerable to obfuscation and evasion techniques. To this end, dynamic approaches utilizing process resource-utilization metrics have emerged as promis...
Huvudupphovsmän: | Dimosthenis Natsos, Andreas L. Symeonidis |
---|---|
Materialtyp: | Artikel |
Språk: | English |
Publicerad: |
Elsevier
2025-03-01
|
Serie: | Results in Engineering |
Ämnen: | |
Länkar: | http://www.sciencedirect.com/science/article/pii/S2590123025003366 |
Liknande verk
Liknande verk
-
Android traffic malware analysis and detection using ensemble classifier
av: A. Mohanraj, et al.
Publicerad: (2024-12-01) -
A Comprehensive Review on Malware Detection Approaches
av: Omer Aslan, et al.
Publicerad: (2020-01-01) -
Android Malware Category and Family Identification Using Parallel Machine Learning
av: Ahmed Hashem El Fiky, et al.
Publicerad: (2022-07-01) -
On the Effectiveness of Perturbations in Generating Evasive Malware Variants
av: Beomjin Jin, et al.
Publicerad: (2023-01-01) -
A New Malware Classification Framework Based on Deep Learning Algorithms
av: Omer Aslan, et al.
Publicerad: (2021-01-01)