Performance Analysis of Machine Learning Algorithms for Malware Detection by Using CICMalDroid2020 Dataset
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Dosyalar
Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
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Yayıncı
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
In parallel with the developments in technology, access to information has become easier. Although this situation has a positive effect on our lives, it is an inevitable fact that information has become a target by malicious people. Theft of information and its use as a threat by these people have caused concerns about information security. Malware developed for these purposes poses a great danger to the security of information. In the face of this situation, which increases as access to information becomes easier, researchers have accelerated their work on detecting and preventing malware and ensuring information security. In the literature, it is seen that the detection of malicious software has been carried out with different studies. In this study, malware detection was carried out using the WEKA program. The effects of different machine learning classifiers, feature extraction and the parameters that affect the performance of the classification that gives the best result were examined in the analyzes made with the CICMalDroid2020 dataset. The results are presented in detail.
Açıklama
Anahtar Kelimeler
Kaynak
Düzce Üniversitesi Bilim ve Teknoloji Dergisi
WoS Q Değeri
Scopus Q Değeri
Cilt
9
Sayı
6
