Author

E. Bayazit

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Conference Jul 2026

A Comparative Analysis of Machine Learning and Deep Learning Methods for Malware Detection in Portable Executable Files

Malware severely threatens cybersecurity through Portable Executable (PE) files. In this study, the performances of machine learning and deep learning models for malware detection are compared using static analysis features extracted from PE files. Tree-based ensemble models like Random Forest, XGBoost, LightGBM, and C...

Gokay Mutlu, Neşe Rihani, E. Bayazit · Signal Processing and Commun... · 0 citations

Open access Jun 2026

A Deep Learning Framework for Three-Dimensional Malware Image Classification

It is shown that multi-dimensional visualization of malware achieves improved classification performance, and the combination of three-dimensional malware visualization, deep learning, and genetic optimization is promising for the development of future intelligent malware detection tools.

Muharrem Aslantas, E. Bayazit, Buket Doğan et al. · Applied Sciences · 0 citations