Research on data fusion and threat alert model of penetration testing in forestry network security situation awareness
林业网络安全态势感知中渗透测试数据融合与威胁预警模型研究

摘要

随着林业资源监测、生态环境评估、智慧林业管理等系统的数字化与联网化程度不断提高，网络攻击手段日益多样化和隐蔽化，传统的安全防护模式难以及时、准确地发现潜在威胁。渗透测试作为评估系统脆弱性的重要技术手段，在态势感知体系中扮演着核心角色。然而，不同来源、不同格式的渗透测试数据在融合分析过程中面临标准不统一、数据冗余和信息孤岛等问题，限制了预警模型的有效性。本研究结合数据融合技术与智能分析方法，构建适用于林业领域的威胁预警模型，以提升风险识别的准确度与响应速度，为林业网络安全保障提供技术支撑。

Abstract

With the increasing degree of digitalization and network of forestry resource monitoring, ecological environment assessment, smart forestry management and other systems, network attack means becoming more and more diversified and concealed, and the traditional security protection model can hardly detect potential threats timely and accurately. Penetration testing, as an important technical means to evaluate vulnerability, plays a central role in the situation awareness system. However, in the process of data integration and analysis, penetration testing data from different sources and in different formats are facing such as inconsistent standards, data redundancy and information islands, which limits the effectiveness of the early warning model. In this study, data fusion technology and intelligent analysis method are combined to construct threat early warning model suitable for the forestry field, so as to improve the accuracy of risk identification and the speed of response, and to provide technical support for the security guarantee of network.