电信科学 ›› 2020, Vol. 36 ›› Issue (6): 125-132.doi: 10.11959/j.issn.1000-0801.2020158

• 研究与开发 • 上一篇    下一篇

一种基于多视角特征融合的Webshell检测方法

林锋1,徐柳婧2,陈晓华3,戚伟强2,陈可2,朱添田4   

  1. 1 浙江经贸职业技术学院信息技术系,浙江 杭州310018
    2 国网浙江省电力有限公司信息通信分公司,浙江 杭州 310007
    3 湖州师范学院信息工程学院,浙江 湖州 313002
    4 浙江工业大学计算机科学与技术学院,浙江 杭州 310023
  • 修回日期:2020-05-15 出版日期:2020-06-20 发布日期:2020-06-18
  • 作者简介:林锋(1979- ),男,浙江经贸职业技术学院信息技术系副教授,主要研究方向为网络安全|徐柳婧(1989- ),女,现就职于国网浙江省电力有限公司信息通信分公司,主要研究方向为信号与信息技术、信息技术管理|陈晓华(1977- ),男,湖州师范学院信息工程学院副教授,主要研究方向为网络资源分配与安全|戚伟强(1984- ),男,现就职于国网浙江省电力有限公司信息通信分公司,主要研究方向为网络安全和信息运维|陈可(1988- ),男,现就职于国网浙江省电力有限公司信息通信分公司,主要研究方向为电力信息技术|朱添田(1992- ),男,博士,浙江工业大学讲师,主要研究方向为网络安全
  • 基金资助:
    国家自然科学基金资助项目(61772026);国家自然科学基金资助项目(U1936215)

Method of Webshell detection based on multi-view feature fusion

Feng LIN1,Liujing XU2,Xiaohua CHEN3,Weiqiang QI2,Ke CHEN2,Tiantian ZHU4   

  1. 1 Department of Science and Technology,Zhejiang Institute of Economics and Trade,Hangzhou 310018,China
    2 Information and Communications Branch,State Grid Zhejiang Electric Power Company,Hangzhou 310007,China
    3 School of Information and Engineering,Huzhou Teachers College,Huzhou 313002,China
    4 College of Computer Science and Technology,Zhejiang University of Technology,Hangzhou 310023,China
  • Revised:2020-05-15 Online:2020-06-20 Published:2020-06-18
  • Supported by:
    The National Natural Science Foundation of China(61772026);The National Natural Science Foundation of China(U1936215)

摘要:

Webshell是一种Web端的恶意脚本文件。它通常由攻击者上传至目标服务器来达成其非法的访问控制的目的。现有Webshell检测方法存在诸多不足,如单一的网络流量行为、简易被绕过的签名比对、单一的正则匹配等。针对上述不足之处,基于PHP语言的Webshell,提出了一种基于多视角特征融合的Webshell检测方法,首先,提取包括词法特征、句法特征、抽象特征在内的多种特征;其次,利用费舍尔评分对特征进行重要程度的排序与筛选;最后,通过 SVM 建立能有效区分 Webshell 和正常脚本的模型。在大规模的实验中,模型对Webshell和正常样本的最终分类精度达到了92.1%。

关键词: Webshell检测, 多视角特征融合, 特征选择与提取, 机器学习

Abstract:

Webshell is a malicious script file on the Web.It is usually uploaded by the attacker to the target server to achieve the purpose of illegal access control.In order to overcome the shortcoming of the existing Webshell detection methods,such as single network traffic behavior,simple by passed signature comparison,and easily bypassed signature comparison,a method of Webshell detection based on multi-view feature fusion for PHP Webshell detecting was proposed.Firstly,multiple features including lexical features,syntactic features,and abstract features were extracted.Secondly,fisher score was used to sort and filter all features according to the degree of importance.Finally,a model that can effectively distinguish Webshell from normal scripts was established through SVM.The large-scale experiment in real-world scenario shows that the final accuracy of our model can reach 92.1%.

Key words: Webshell detection, multi-view feature fusion, feature selection and filtering, machine learning

中图分类号: 

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