Recognition Method of Fishing Web Pages Based on Decision Tree
WEI Sheng-na;SHENG Chao;Information Engineering Institute, East China University of Technology;
Now many criminals use phishing sites to steal the user's personal information, steal the user's property, causing huge losses to the user. Therefore, this paper uses the decision tree learning algorithm to extract the keywords, analyze and establish the phishing website feature model, and judge the unknown website. CART is a decision tree algorithm, but the majority voting method of CART decision tree will shield the influence of small class data type. Therefore, this paper improves the CART decision tree according to this point, introduces the cost function, and makes use of iteration and minimum mean square error Adjust the weight of the feature to increase the penalty. The experimental results show that the improved decision tree has successfully reduced the error rate of negative samples and improved the recognition rate in the analysis of unknown websites.
【CateGory Index】： TP393.092