Detection Method for Hidden Hyperlink Based on Machine Learning
摘要
In the era of big data,traditional hidden hyperlink detection technology cannot quickly and accurately identify websites that encounter “hidden hyperlink attacks” on massive Web pages.To solve this problem,this paper introduces machine learning to the detection method for hidden hyperlink,which combines the characteristics of hidden hyperlink related texts,hidden hyperlink domains and the hidden structure of hidden hyperlink.The three models are constructed and compared using Classification and Regression Tree (CART),Gradient Boosted Decision Tree (GBDT) and Random Forest (RF).based on the proposed method.Experimental results show that the proposed method has high accuracy and reliability,and the classification accuracy of the detection model constructed by RF can reach 0.984.