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...
Saved in:
Main Authors: | Dimosthenis Natsos, Andreas L. Symeonidis |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2025-03-01
|
Series: | Results in Engineering |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025003366 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Detecting Obfuscated Malware Infections on Windows Using Ensemble Learning Techniques
by: Yadigar Imamverdiyev, et al.
Published: (2025-01-01) -
MALVADA: A framework for generating datasets of malware execution traces
by: Razvan Raducu, et al.
Published: (2025-05-01) -
MalHAPGNN: An Enhanced Call Graph-Based Malware Detection Framework Using Hierarchical Attention Pooling Graph Neural Network
by: Wenjie Guo, et al.
Published: (2025-01-01) -
LinRegDroid: Detection of Android Malware Using Multiple Linear Regression Models-Based Classifiers
by: Durmus Ozkan Sahin, et al.
Published: (2022-01-01) -
Apk2Audio4AndMal: Audio Based Malware Family Detection Framework
by: Oguz Emre Kural, et al.
Published: (2023-01-01)