通信学报 ›› 2016, Vol. 37 ›› Issue (2): 89-98.doi: 10.11959/j.issn.1000-436x.2016034

• 学术论文 • 上一篇    下一篇

面向网络环境的SQL注入行为检测方法

赵宇飞1,熊刚2,贺龙涛3,李舟军1   

  1. 1 北京航空航天大学计算机学院,北京 100083
    2 中国科学院信息工程研究所,北京 100093
    3 国家计算机网络应急技术处理协调中心,北京 100029
  • 出版日期:2016-02-26 发布日期:2016-02-26
  • 基金资助:
    国家高技术研究发展计划(“863”计划)基金资助项目;国家自然科学基金资助项目;国家自然科学基金资助项目;教育部博士点基金资助项目;国家科技支撑计划基金资助项目;国家科技支撑计划基金资助项目;中国科学院战略性先导科技专项课题基金资助项目

Approach to detecting SQL injection behaviors in network environment

Yu-fei ZHAO1,Gang XIONG2,Long-tao HE3,Zhou-jun LI1   

  1. 1 School of Computer Science, Beihang University, Beijing 100083, China
    2 Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China
    3 National Computer Network Emergency Response Technical Team/Coordination Center of China, Beijing 100029, China
  • Online:2016-02-26 Published:2016-02-26
  • Supported by:
    The National High Technology Research and Development Program of China (863 Program);The National Natural Science Foundation of China;The National Natural Science Foundation of China;The National Natural Science Foundation of China;The National Natural Science Foundation of China;The National Key Technology R&D Program;The Strategic Priority Research Program of the Chinese Academy of Sciences

摘要:

SQL 注入攻击是 Web 应用面临的主要威胁之一,传统的检测方法针对客户端或服务器端进行。通过对SQL注入的一般过程及其流量特征分析,发现其在请求长度、连接数以及特征串等方面,与正常流量相比有较大区别,并据此提出了基于长度、连接频率和特征串的LFF(length-frequency-feature)检测方法,首次从网络流量分析的角度检测SQL注入行为。实验结果表明,在模拟环境下,LFF检测方法召回率在95%以上,在真实环境下,该方法也取得较好的检测效果。

关键词: Web安全, SQL注入, 网络流量, 异常检测

Abstract:

SQL injection attack is one of the main threats that many Web applications faced with. The traditional detection method depended on the clients or servers. Firstly the process of SQL injection attack was analyzed, and then the differences between attack traffic and normal traffic HTTP request length, HTTP connections and feature string were discovered. Based on the request length, request frequency and feature string, a new method, LFF (length-frequency-feature), was proposed to detect SQL injection behaviors from network traffic. The results of experiments indicated that in simulation environments the recall of LFF approach reach up to 95%, and in real network traffic the LFF approach also get a good detection result.

Key words: Web security, SQL injection, network traffic, outlier detection

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