计算机与现代化

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一种基于网络流量分析的快速木马检测方法

  

  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:2019-03-25 出版日期:2019-06-14 发布日期:2019-06-14
  • 作者简介: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; 郭春(1986-),男,贵州贵阳人,副教授,博士,研究方向:网络与信息安全; 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,E-mail: jiangchaohui@126.com。
  • 基金资助:
    国家自然科学基金资助项目(61540049); 贵州省科技计划项目([2017]1051,[2018]3001); 贵州省公共大数据重点实验室开放课题(2017BDKFJJ025); 河南省科技攻关计划项目(182102210123)

A Fast Trojan Detection Method Based on Network Traffic Analysis

  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:2019-03-25 Online:2019-06-14 Published:2019-06-14

摘要: 木马程序作为一种窃密工具,常在APT(Advanced Persistent Threat)攻击中被使用,其对网络空间的安全造成了严重的危害。对木马的检测也受到了研究者的广泛关注,研究者提出了许多基于网络流量分析的检测方法,然而目前的方法一般都需要分析完整的通信流量,因此会造成一定的检测延迟,从而导致防御措施不能及时被部署。为了尽早地保护内部敏感信息不被泄露,本文仅使用木马通信连接建立后的前5个数据包来抽取流量特征,并以此构建木马通信会话快速检测模型。实验结果表明,本文方法在分析通信早期数据的情况下,获得了较高的准确率和较低的误报率,验证了本文方法的有效性。

关键词: 木马检测, 网络流量分析, 特征分析, 远控型木马

Abstract: As a stealing tool, Trojans are often used in APT(Advanced Persistent Threat) attacks, which causes a serious hazard to the security of cyberspace. The detection of Trojans has also received extensive attention from researchers. At present, researchers have proposed many detection methods based on network traffic analysis. However, these methods generally need to analyze complete communication traffic, so it will cause certain detection delay and cause that the defense measures cannot be deployed in time. In order to protect the internal sensitive information from being leaked as early as possible, this paper analyzes the traffic characteristics of the Trojan communication and extracts the traffic features from the first five packets after the communication being established, and then constructs a rapid detection model of Trojan communication session. The experimental results show that the proposed method obtains higher accuracy and lower false positive rate when analyzing the early data of communication, which verifies the effectiveness of the proposed method.

Key words: Trojan detection, network traffic analysis, characteristics analysis, remote access Trojan

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