Classificacção de Ransomware utilizando Algoritmos de Machine Learning

Ransomware is a subset of malware that is growing as a serious cyber threat. This malicious software prevents orlimits users from accessing their system until the ransom is paid.The use of Machine Learning (ML) algorithms has been widely used in automatic classification of these attacks. In this paper,we apply the Principal Component Analysis (PCA) techniqueas feature extraction intending to reduce dimensionality of the dataset, then we explore 11 ML algorithms in order to findthe best classifier for ransomware detection. Five comparisonmethods used in the literature were discussed. Nayes Bayesmethod achieved an Accuracy of 100% in one of the methods.