基于多尺度加权特征融合的网络信息安全风险识别方法  

Network Information Security Risk Identification Method Based on Multi-scale Weighted Feature Fusion

作　　者：吴秦鹏 WU Qinpeng(State Grid Xingping Power Supply Company,Xingping 713100,China)

机构地区：[1]国网兴平市供电公司,陕西兴平713100

出　　处：《通信电源技术》2023年第13期19-21,共3页Telecom Power Technology

摘　　要：现有网络信息安全风险识别方法在实际应用中存在识别所用时间较长、识别准确性较低的问题,引入多尺度加权特征融合,并开展对其风险识别方法的设计研究。在网络空间环境中构建一个数据挖掘模型,采集网络信息安全风险数据。基于多尺度加权特征融合,对电力安全生产风险分类通过窗口函数、特征函数进行计算,预测网络信息攻击路径,并实现对网络信息安全风险的识别。通过对比实验证明,新的识别方法与现有识别方法相比,能保证识别结果具备极高的准确性,促进网络信息安全性的提高。In view of the problems that the existing network information security risk identification methods take a long time to identify and have low accuracy in practical application,multi-scale weighted feature fusion is introduced to carry out the design and research of its risk identification methods.A data mining model is constructed in the network space environment to collect network information security risk data.Based on multi-scale weighted feature fusion,the safety production risks of electric power are classified.Finally,through the calculation of window function and characteristic function,the network information attack path is predicted and the network information security risk is identified.Through comparative experiments,it is proved that compared with the existing recognition methods,the new recognition method takes less time,and can ensure that the recognition results have high accuracy,and promote the improvement of network information security.

关 键 词：多尺度 网络信息 加权特征 安全风险 融合 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术]