Open access
Aug 2026
Machine Learning-Based Malware Detection: A Comparative Study of Random Forest, Decision Tree, KNN, and Linear SVM
Random Forest achieves the highest performance with a test accuracy of 96.3%, F1-score of 0.947, and AUC of 0.993, establishing it as the optimal algorithm for static malware detection tasks and establishing it as the optimal algorithm for static malware detection tasks.
Umesh Balami, Ganesh Gautam, Gajendra Sharma
· American Journal of Agricult... · 0 citations