A Static Malicious Javascript Detection Using SVM

摘要：

　　primary threats of the network security.JavaScript is not only a browser scripting language that allows developers to create sophisticated client-side interfaces for web applications; but also used to carry out attacks taht used to steal users credentials and lure users into providing sensitive information to unauthorized parties.We propose a static malicious JavaScript detection techniques based on SVM(Support Vector Machine).Our approach combines static detection with machine learning technique,to analyze and extract malicious script features,and use the machine learning technology,SVM,to classify the scripts.This technique has the characteristics of high detection rate,low false positive rate and the detection of unknown attacks.Applied to experiments on the prepared data set,we achieved excellent detection performance.

关键词： SVM static detection malicious script detection

作者: WANG Wei-Hong LV Yin-Jun CHEN Hui-Bing FANG Zhao-Lin WANG Wei-Hong LV Yin-Jun CHEN Hui-Bing FANG Zhao-Lin

作者单位: Zhejiang University of Technology HangZhou,China

会议类型: 国际会议

会议名称: 2013 2nd International Conference on Computer Science and Electronics Engineering(ICCSEE2013)(2013年第二届计算机科学与电子工程国际会议)

会议地点: 杭州

会议语种:英文

页码: 214-217

在线出版日期: 2013-03-22（万方平台首次上网日期，不代表论文的发表时间）