使用机器学习技术识别Web攻击者  

Identifying Web Attackers using Machine Learning Techniques

作　　者：杨美月 钟楠宇 吴嘉熙 唐屹[2] YANG Mei-yue;ZHONG Nan-yu;WU Jia-xi;TANG Yi(School of Mathematics and Information Science,Guangzhou University,Guangzhou 510006,China;Guangdong Provincial Key Laboratory Co-sponsored by Province and City of Information Security Technology,Guangzhou University,Guangzhou 510006,China)

机构地区：[1]广州大学数学与信息科学学院,广东广州510006 [2]广州大学广东省信息安全技术省市共建重点实验室,广东广州510006

出　　处：《电脑知识与技术》2019年第7Z期237-240,共4页Computer Knowledge and Technology

基　　金：广东省自然科学基金重大基础研究培育项目(2015A030308016);广东省普通高校创新团队建设项目(2015KCXTD014)

摘　　要：随着Web应用程序的广泛应用,攻击者对Web应用程序的攻击也层出不穷。若能够识别应用程序的攻击者,就可以有效地帮助系统管理员设计出有针对性的防御方法。以识别跨站脚本攻击(XSS)的攻击者为例,提出一种基于机器学习的XSSer-FP方法识别Web应用程序的攻击者。该方法通过分析带攻击代码的URL特征来识别XSS攻击者。实验结果证明了该方法应用于Web攻击者识别的可行性。With the wide application of Web applications,the attacks on these Web applications emerge in an endless stream.If the attacker of the application can be identified,it can effectively help the system administrators design targeted defense method.Tak?ing identifying the attacker of Cross-Site Scripting(XSS)as an example,an XSSer-FP method based on machine learning is pro?posed to identify the attackers of Web application.This method identifies XSS attackers by analyzing URL characteristics with at?tack codes.Experimental results proved the feasibility of this method in Web attacker identification.

关 键 词：XSS攻击 机器学习 URL 攻击者识别 攻击溯源 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术]