An Efficient Approach to Detecting Phishing Web

As the electronic commerce and on-line trade expand, phishing has already become one of the several forms of network crimes. This paper presents an automatic approach for intelligent phishing web detection based on learning from a large number of legitimate and phishing webs. As given a web, its Uniform Resource Locator (URL) features are first analyzed, and then classified by Naive Bayesian (NB) classifier. When the web's legality is still suspicious, its webpage is parsed into a document object model tree, and then classified by Support Vector Machine (SVM) classifier.