Article Detail

Tuğba KARACAK

Keywords

Malware Detection Machine Learning Virusshare

Doi : 10.5281/zenodo.18664515

Abstract

Cybersecurity is one of the most critical areas in the digital world today, as computer systems, networks, and data are constantly exposed to malicious attacks; these attacks lead to serious consequences such as financial losses, data breaches, service disruptions, and reputational damage. malware represents the most significant element of this threat, encompassing various types such as trojans, worms, ransomware, and spyware, and it complicates traditional signature-based detection methods by continuously transforming itself through polymorphic and metamorphic techniques. In this study, research has been conducted on the detection of malware using machine learning models, and the performances of these models have been compared.

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