Scientific Development Research

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.

Forestry network security; Situation awareness; Test data fusion; Threat early warning model