Review and evaluation of selected malware detection methods
Abstract
In the face of the growing threat of cyberattacks and increasingly sophisticated malware, effective detection is a key element of IT security. This article presents a comprehensive overview of malware detection methods, ranging from classic signature, heuristic and behavioral techniques, through statistical models and graph theory models, to modern solutions based on deep learning. The primary goal of the article is to qualitatively compare various detection methods based on literature data. The result of this comparison is to demonstrate the potential of formal, mathematical methods in improving the efficiency and accuracy of malware detection.
Fields of Study & Subjects
Advanced Malware Detection Techniques
Security and Verification in Computing
Spam and Phishing Detection
Publication details
- Journal / source
- Przegląd Teleinformatyczny
- Volume
- 12(30)
- Issue
- 1-4
- Pages
- 101–121
- Publication date
- 15 March 2026
- Language
- EN