Detecting the Phishing Website with the Highest Accuracy

Phishing attacks are increasing and it becomes necessary to use appropriate response methods respond effectively phishing attacks. This paper aims uncover attack sites by analyzing a three-module set prevent damage reconsider the awareness of Based on analyzed content, countermeasure was proposed for each type using website features. These features will be classified in order determine effectiveness countermeasure. Finally, method enhanced site security as anti-phishing technology. The detection used three classification algorithms, which decision tree; supporting vector machine random forest were combined into one system that this purpose obtaining highest accuracy detecting sites. results algorithm showed 98.52% higher than others.