基于数据融合的网络安全态势评估

Mixia Liu, Qiuyu Zhang, Zhao Hong, Dongmei Yu
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引用次数: 28

摘要

网络安全态势评估可以通过描述当前状态来预测网络的下一步行为。来自IDS、防火墙和其他安全工具的安全事件目前正在快速增长。然而,大多数入侵事件的研究都集中在IDS警报上,忽略了其他安全工具的入侵证据,或者是将各种安全工具简单地集成在一起,而不影响整个网络的状态。本文从系统的角度对网络安全进行了描述。首先,分析网络态势要素。其次,研究了二者的相关性,提出了网络安全态势的体系结构。第三,分析了多传感器相关算法,其中彩色Petri网用于描述新事件发生后系统状态的变化,D-S证据理论用于组合不同的证据。然后,报告了DARPA 2000 DDoS攻击场景下的实验结果并进行了分析。最后,对本文的工作进行了总结,并提出了下一步的研究目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Network Security Situation Assessment Based on Data Fusion
Network security situation assessment can project the next behavior of the network by describing the current state. Security events from IDS, firewall, and other security tools are currently growing at a rapid pace. However, most intrusion event researches focus on IDS alerts, overlooking other intrusion evidence from other security tools, or they make simple integration of various security tools not inflecting the whole network state. In this paper, we described network security from the view of system. First, network situation elements are analyzed. Second, we research their correlations and present system architecture of network security situation. Third, multi-sensor correlation algorithms are analyzed that colored Petri net is used for describing the changing of system state after arrival of new events and D-S theory of evidence is used for combining the different evidence. Then, we report the experimental results on the DARPA 2000 DDoS attack scenarios and analyze them. At last, we conclude our work and present next research goal.
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