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基于T_NAG模型的攻击路径预测方法研究 被引量:3

Research on attack path prediction method based on T_NAG model
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摘要 为了更好地刻画攻击者的攻击轨迹,设计出一种基于T_NAG(time attribute network attack graph)模型的路径预测方法。首先,提出新的攻击图模型T_NAG,根据实时行为轨迹对攻击者能力加以区分;其次,依据攻击者具有不同能力的特性,提出攻击意向的概念,统筹考虑操作风险与攻击收益,将时间衰减参数引入到攻击意向计算中,并设计出一种基于攻击者能力的漏洞利用率量化方法;最后,将攻击意向与漏洞利用率进一步融入到对路径可达概率的考量中,给出预测攻击路径的IntenAbi-PathPre算法。实验结果表明,该方法可以有效去除攻击图中的冗余,并且使攻击路径预测的准确性得到明显提高。 In order to depict the attacker’s attack trajectory better,this paper proposed a path prediction method based on T_NAG(time attribute network attack graph)model.First of all,it proposed a new attack graph model T_NAG to distinguish the attacker’s ability according to the real-time behavior trace.Secondly,according to the characteristics of the attacker’s different capabilities,it proposed the concept of attack intention,considered the operation risk and attack profit as a whole and introduced the time decay parameter into the intention calculation,and designed a vulnerability utilization quantification me-thod based on the attacker’s capabilities.Finally,it further integrated attack intention and vulnerability utilization into the consideration of path reachability probability,and gave the IntenAbi-PathPre algorithm to predict the attack path.The experimental results show that this method can effectively remove the redundancy in the attack graph and improve the accuracy of attack path prediction.
作者 翟海霞 卢月萌 王辉 敖山 Zhai Haixia;Lu Yuemeng;Wang Hui;Ao Shan(College of Computer Science&Technology,Henan Polytechnic University,Jiaozuo Henan 454003,China)
出处 《计算机应用研究》 CSCD 北大核心 2021年第3期886-892,共7页 Application Research of Computers
基金 国家自然科学基金资助项目(61300216) 全国教育科学规划教育部重点课题资助项目(DFA170292) 河南省软科学研究计划资助项目(182400410147) 河南省科技攻关(社会发展领域)资助项目(182102310946)。
关键词 攻击图 路径预测 攻击者意向 路径可达性 attack graph path prediction attacker’s will path accessibility
作者简介 翟海霞(1976-),女,河南济源人,副教授,硕导,博士,主要研究方向为网络安全;通信作者:卢月萌(1995-),女,河南南阳人,硕士研究生,主要研究方向为网络安全(347351225@qq.com);王辉(1975-),男,河南焦作人,副教授,硕导,博士,主要研究方向为计算机网络及网络安全等;敖山(1971-),男,四川丰都人,副教授,硕导,博士,主要研究方向为网络安全.
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