Güç spektral yoğunluğuna (PSD) dayalı veri madenciliği teknikleri kullanarak otomatik kötü amaçlı yazılım tespiti

A malware is a software that furtively achieves its process below the appearance of genuine software. classic methods apply signatures to distinguish these software's denote tiny risk to new and hidden examples whose signatures are not offered. The emphasis of malware investigation is unstable from applying signature designs to classifying the malicious conduct showed by this malware. Numerous data mining methods proposed to notice malware mechanically in the effectual face. In this thesis, Power Spectral Density (PSD) applied to extract the features of malware dataset and the yield of PSD confidential applying several of data mining methods: Support Vector Machine (SVM), Radial Basis Network (RBF) and multi-layer perceptron (MLP). These techniques presented remarkable results when compared with common researches in this field. Keywords: Malware, Data mining, Power spectral density, computer security.