Comparisons of machine learning techniques for detecting malicious webpages
3 supervised and 2 unsupervised techniques are modeled to detect malicious webpages. Supervised machine learning (ML) techniques accuracies are above 89%. Unsupervised ML techniques accuracies have at least a silhouette coefficient of 0.87. Information obtained from URLs, page links, semantics and visual features of webpages. Chrome extension, lightweight and heavyweight classifiers and online learning are used.
k-nearest neighbor support vector machine naive bayes affinity propagation k-means supervised and unsupervised learning