For each year

phishing website in electronic commerce

communications

banking and other areas to give users a great loss

so successfully and effectively prevent phishing website become a difficult task. In this paper

through the analysis of the actual data

extracts 2 kinds of characteristics such as the characteristics of URL

webpage text content to describe the page

classifiers are then built based on these different feature representations

and optimized based on the theory of incremental learning

the online learning ability of the algorithm is improved. Finally

the classification ensemble method is used to synthesize the prediction results of each classifier

which can achieve the goal of online intelligent detection for phishing website. According to the experimental results

the ensemble classification has good online learning ability and generalization ability.