信息网络安全

信息网络安全 ›› 2016, Vol. 16 ›› Issue (12): 28-33.doi: 10.3969/j.issn.1671-1122.2016.12.005

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基于特征的网络漏洞态势感知方法研究

高川1, 严寒冰2, 贾子骁2   

  1. 1.北京航空航天大学计算机学院,北京 100191
    2.国家计算机网络应急技术处理协调中心,北京 100020
  • 收稿日期:2016-09-12 出版日期:2016-12-20 发布日期:2020-05-13
  • 作者简介:

    作者简介：高川（1990—）,男,山东,硕士研究生,主要研究方向为网络安全;严寒冰（1975—）,男,江西,高级工程师,博士,主要研究方向为反垃圾邮件、图像处理与分析、网络安全、网络攻防技术、海量数据检索;贾子骁（1986—）,男,山西,工程师,博士,主要研究方向为计算机网络、网络安全。

  • 基金资助:
    国家科技支撑计划[2015BAK21B01]

Research on the Method for Network Vulnerabilities Situational Awareness Based on the Features

Chuan GAO1, Hanbing YAN2, Zixiao JIA2   

  1. 1. College of Computer, Beihang University, Beijing 100191, China
    2. National Computer Network Emergency Response Technical Team/Coordination Center of China, Beijing 100020, China
  • Received:2016-09-12 Online:2016-12-20 Published:2020-05-13

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摘要：

随着互联网规模的持续扩大,互联网安全问题日益严峻,互联网设备和应用的安全态势成为所有网络用户重视的内容。文章提出一种基于特征的互联网设备和应用的测量方法。首先,对设备和应用进行特征提取,采用主动探测和被动监测相结合的方法,得到设备和应用的信息。然后,对得到的信息进行分析,描绘互联网设备和应用的漏洞分布态势。文章对3种设备和应用进行测量,验证了该方法,探测了它们的漏洞分布情况。漏洞分布态势图可以帮助网络管理员有效理解互联网设备和应用的状态,及时发现漏洞并进行修补。

关键词: 特征提取, 主动探测, 被动监测, 安全态势

Abstract:

With the continuous development of the Internet, the security problems of the Internet are more and more serious. The security situations of the Internet devices and applications have gotten Internet users’ more attentions. This paper puts forward a measurement method of the Internet devices and applications based on the features. Firstly, the features of the Internet devices and applications are extracted. By combining the methods of active detection and passive monitoring, the information of the Internet devices and applications is obtained. Then by analyzing the information of the Internet devices and applications, the paper depicts the vulnerabilities distribution situations of the Internet devices and applications. The paper verifies the method by measuring three different Internet devices and applications, and detects their vulnerabilities distribution situations, which can help the administrators understand the situations of the Internet devices and applications effectively, and find vulnerabilities and repair them in time.

Key words: features extraction, active detection, passive monitoring, security situation

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