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...
Hauptverfasser: | Dimosthenis Natsos, Andreas L. Symeonidis |
---|---|
Format: | Artikel |
Sprache: | English |
Veröffentlicht: |
Elsevier
2025-03-01
|
Schriftenreihe: | Results in Engineering |
Schlagworte: | |
Online Zugang: | http://www.sciencedirect.com/science/article/pii/S2590123025003366 |
Ähnliche Einträge
Ähnliche Einträge
-
Android traffic malware analysis and detection using ensemble classifier
von: A. Mohanraj, et al.
Veröffentlicht: (2024-12-01) -
A Comprehensive Review on Malware Detection Approaches
von: Omer Aslan, et al.
Veröffentlicht: (2020-01-01) -
Android Malware Category and Family Identification Using Parallel Machine Learning
von: Ahmed Hashem El Fiky, et al.
Veröffentlicht: (2022-07-01) -
On the Effectiveness of Perturbations in Generating Evasive Malware Variants
von: Beomjin Jin, et al.
Veröffentlicht: (2023-01-01) -
A New Malware Classification Framework Based on Deep Learning Algorithms
von: Omer Aslan, et al.
Veröffentlicht: (2021-01-01)