基于免疫危险理论的网络安全态势定量感知模型

Immune danger theory based quantitative model for network security situation awareness

针对基于免疫的异常入侵检测技术自体/非自体区分困难、漏报误报率高而导致网络安全态势感知结果不准确的问题,受免疫危险理论启发,提出了一个新的网络安全态势感知模型。模型采用分布式结构设计,部署在主机上的传感器利用人工抗体实时检测网络攻击,并依据攻击类别和频度计算危险信号大小;模型中的安全态势评估中心通过分析、融合来自主机的多数据源危险信号,进而定量感知主机和整个网络的安全态势。理论分析和仿真结果表明该模型是有效的,并解决了网络安全类的人工免疫系统难以区分自体/非自体之不足,为实时、定量感知网络安全态势提供了一个新思路。

The danger theory is changing the traditional thinking ways of self/non-self discrimination.Aiming at the deficiencies of the immunity based security situation awareness method,this paper proposed an immune danger theory based quantitative model for network security situation awareness（DTQMSA）.The mode architecture was distributed.The host-based located sensors were in charge of the detection of network attacks and the computation of danger signal.The network security situation was obtained through fusing and analyzing the multi danger signal coming from each computer host.Theoretical analysis and simulation results show that the proposed model is valid.Thus,it provides a good solution to network security situation awareness quantitatively and in real time.