Detection of Phishing URL using Bayesian Optimized SVM Classifier

This paper aims to collect, map and model elements that will lead to the finding of phishing UR automatically, for this purpose data mining is used as a basic tool and in this sense, it is considered that the existing patterns in a URL will make it possible to distinguish the legitimate link for pages. Whereas, the identification of these patterns will serve to model a successful classification method. For this purpose, the attributes found in the database “phishing web” that correspond to patterns of phishing pages will be validated, at the same time it will be evaluated algorithms extracted from the literature that allow a better classification of records, finally, a model with the highest precision results is delivered and it consists of Bayesian optimized support vector machine classifier.