Phishing Website Detection Based on Machine Learning Algorithm

Phishing websites are a means to deceive users' personal information by using various means to impersonate the URL address and page content of a real website. This paper analyzes the structural features of the URL of the phishing website, extracts 12 kinds of features, and uses four machine learning algorithms for training. Then, use the best performing algorithm as our model to identify unknown URLs. After the recognition is completed, a snapshot of the web page is extracted and compared with the regular web page snapshot to implement the recommendation of the original regular web page of the phishing web page.