计算机与现代化

• 信息安全 • 上一篇    下一篇

一种基于HTTP协议的隐蔽隧道及其检测方法

  

  1. (1.贵州大学计算机科学与技术学院,贵州贵阳550025;2.贵州省公共大数据重点实验室,贵州贵阳550025)
  • 收稿日期:2019-03-05 出版日期:2019-06-14 发布日期:2019-06-14
  • 作者简介:赵琦(1990-),女,河南许昌人,硕士研究生,研究方向:信息安全,E-mail: 932692974@qq.com; 蒋朝惠(1965-),男,四川广安人,教授,硕士,研究方向:网络与信息安全; 周雪梅(1977-),女,贵州贵阳人,讲师,硕士,研究方向:网络安全,入侵检测技术; 宋紫华(1994-),男,四川广元人,硕士研究生,研究方向:网络与信息安全,E-mail: sc_zhsong@163.com。
  • 基金资助:
    贵州省公共大数据重点实验室开放课题(2017BDKFJJ025)

A Covert Tunnel Based on HTTP Protocol and Its Detection Method

  1. (1. College of Computer Science and Technology, Guizhou University, Guiyang 550025, China;
    2. Guizhou Provincial Key Laboratory of Public Big Data, Guiyang 550025, China)
  • Received:2019-03-05 Online:2019-06-14 Published:2019-06-14

摘要: 隐蔽隧道攻防博弈已有三十多年,现有隐蔽隧道的主要检测方法包括对报文数据与报文结构的检测、基于流量统计的检测和基于机器学习的检测等。随着相关技术的发展,越来越多的隐蔽隧遂通过应用层协议构建。本文首先设计一种基于HTTP协议通信的隐蔽隧道,隧道使用后门程序进行隐蔽通信,并对通信数据进行加密使其具有更高的隐蔽性,实验表明该隧道可以绕过防火墙、360卫士等安全设备。其次,分析该类隧道结构和流量特征并提出一种检测方法,分别对报文结构特征和统计特征提取高区分度的特征。最后,选取机器学习的方法进行检测,实验使用SVM和决策树都可以准确地检测出该类隐蔽隧道,并且具有较低的误报率和漏报率。

关键词: 隐蔽隧道, webshell, 机器学习

Abstract: The attack-defense game of covert tunnels has lasted for more than 30 years. The main detection methods of existing covert tunnels include the detection of message data and structure, detection based on flow statistics and detection based on machine learning. With the development of relevant technologies, more and more covert tunnes are constructed through the application layer protocol. Firstly, this paper designs a covert tunnel based on HTTP protocol. The tunnel uses backdoor program to carry out concealed communication, and encrypts the communication data to make it more concealed. The experiment shows that the tunnel can bypass the firewall, 360 guard, and other security equipments. Secondly, this paper analyzes the structure and flow characteristics of this type of tunnel and proposes a detection method to extract high-distinction features for the structural features and statistical features of the message. Finally, machine learning method is selected for detection. Both SVM and decision tree can accurately detect this kind of covert tunnel, and have low false alarm rate and missing alarm rate.

Key words: covert tunnel, webshell, machine learning

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