计算机与现代化 ›› 2020, Vol. 0 ›› Issue (10): 110-115.

• 网络与通信 • 上一篇    下一篇

时间Petri网在渗透测试中的应用

  

  1. (1.中国人民解放军91404部队,河北秦皇岛066000;2.江苏自动化研究所,江苏连云港222061)
  • 出版日期:2020-10-14 发布日期:2020-10-14
  • 作者简介:李海浩(1982—),男,河北保定人,工程师,硕士,研究方向:武器装备软件测评,自动化测试,E-mail: 93685670@qq.com; 吴亚锋(1990—),男,江苏宿迁人,助理工程师,硕士,研究方向:软件质量与可靠性,自动化测试,E-mail: 47214866@qq.com; 王晓强(1988—),男,河北承德人,工程师,硕士,研究方向:软件质量与可靠性,自动化测试,E-mail: 93767072@qq.com。
  • 基金资助:
    国家自然科学基金资助项目(61773384)

Application of Timed Petri Net in Penetration Testing

  1. (1. Unit 91404 of the Chinese People’s Liberation Army, Qinhuangdao 066000, China;
    2. Jiangsu Automation Research Institute, Lianyungang 222061, China)
  • Online:2020-10-14 Published:2020-10-14

摘要: 渗透测试攻击模型作为渗透测试的重要环节,受到学术界和工业界的共同关注。现有的渗透测试攻击模型未考虑渗透测试攻击过程中的动态参数,无法描述漏洞的发生时间。本文以漏洞为基本单元,以时间Petri网中库所的时间区间表示漏洞的发生区间,构建以时间Petri网为基础模型的渗透测试攻击模型。首先,将漏洞列表作为输入来构建单漏洞模型;然后,将单漏洞模型集合通过模型整合算法形成完整的渗透测试攻击模型;最后,给出渗透攻击路径选择算法,并通过模拟实验验证本文所提渗透攻击路径选择算法的有效性。

关键词: 时间Petri网, 渗透测试, 单漏洞模型

Abstract: As an important part of penetration testing, the penetration test attack model has attracted the common attention of academia and industry. Existing penetration test attack models do not take into account the dynamic parameters in the penetration test attack process, and cannot describe when the vulnerability occurred. Taking the vulnerability as the basic unit, and the time interval of the place in the timed Petri net representing the occurrence interval of the vulnerability, this paper builds a penetration test attack model based on the timed Petri net. First, the vulnerability list is used as input to build a single vulnerability model. Then, the single vulnerability model collection is used to form a complete penetration test attack model through a model integration algorithm. Finally, the algorithm of penetration attack path selection is given, and the effectiveness of the algorithm of penetration attack path selection proposed in this paper is verified by simulation experiments.

Key words: timed Petri net, penetration test, vulnerability model