Murat Dener*, Sercan Gulburun
CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1235-1251, 2023, DOI:10.32604/cmc.2023.036357
Abstract One of the most common types of threats to the digital world is malicious software. It is of great importance to detect and prevent existing and new malware before it damages information assets. Machine learning approaches are used effectively for this purpose. In this study, we present a model in which supervised and unsupervised learning algorithms are used together. Clustering is used to enhance the prediction performance of the supervised classifiers. The aim of the proposed model is to make predictions in the shortest possible time with high accuracy and f1 score. In the first stage of the model, the… More >
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