中文摘要：

为了分析网络威胁的演化趋势，并探讨安全态势的自主感知和调控问题，将跨层结构和认知环融入模型的设计，提出一种基于融合的网络安全态势认知感控模型，增强网络安全系统的层间交互和认知能力．在分析模型组件及其功能的基础上，利用多源融合算法得到各异质传感器对网络安全事件的准确决策，结合对安全事件威胁等级和威胁因子关系的推演，克服威胁因子获取过程中需处理网络组件间复杂隶属关系的不足，从而提出包含服务级、主机级和网络级的层次化态势感知方法，提高对网络威胁的表达能力．而且通过对态势感知曲线的分析，搭建离散计算和连续控制之间的桥梁，形成闭环反馈控制结构，解决安全态势自感知和自调控的问题．仿真实验结果表明：基于融合的网络安全态势认知感控模型及方法能够融合异质安全数据，动态感知威胁的演化趋势，并具有一定的自主调控能力．达到了认知感控的研究目的．为监控和管理网络提供了新的方法和手段．

英文摘要：

For the purpose of exploring the evolution trend and analyzing the autonomous awareness and control problems, this paper proposes a cognitive awareness-control model for network security situation based on fusion. This model is characterized by the design of the cross-layer architecture and cognitive circle which can improve the interactive and cognitive ability between the different network layers. Based on the analysis of the model components and their functions, this paper uses the fusion algorithm to obtain the accurate decision on the security events made by heterogeneous multi-sensor. Combining with the reasoning of the relation between threat gene and threat level, a hierarchical quantification method is put forward, encompassing service layer, host layer and network layer. This approach has the advantage of overcoming the shortcoming of dealing with the complex memberships among network components and improving the expression ability against network threat. In addition, through establishing the bridge between dispersed computing and the continuous control, the close-up feedback structure is formed and the self-awareness and self-control problems are solved. The simulation experiments prove that the presented model and algorithms can fuse heterogeneous security data, dynamically perceive the evolution trend of network threat and possess the autonomous regulation and control ability. This study meets the research goal of cognitive awareness-control and it provides a new method of monitoring and administrating the networks.