物联终端安全态势异常监测方法研究
Research on abnormal monitoring method of IoT terminal security situation
常星 1赵春光 2吴鑫 1赵亮1
作者信息
- 1. 中国科学院沈阳计算技术研究所有限公司,沈阳 110168
- 2. 南瑞集团有限公司(国网电力科学研究院有限公司),南京 210061;北京科东电力控制系统有限责任公司,北京 100192
- 折叠
摘要
针对物联终端安全态势异常监测准确率不高的问题,提出基于指纹特征识别的物联终端安全态势异常监测方法.提取数据包传送过程中的特征信息元,确定物联终端中的传输特征,构建物联终端型号分类特征指纹库;根据指纹特征库中的样本,进行物联终端安全态势异常现象的假设检验识别,最终实现物联终端安全态势异常监测.实验结果表明,所研究方法可有效监测物联终端安全态势异常状态,监测准确率高于85％,充分验证了该方法的应用价值.
Abstract
To solve the problem of the low accuracy of IoT terminal security situation anomaly monitoring,a method of IoT terminal security situation anomaly monitoring based on fingerprint feature recognition is pro-posed.The characteristic information elements are exacted in the process of data packet transmission,and the transmission characteristics in the IoT terminal are determined to construct the model classification fea-ture fingerprint database of the IoT terminal.According to the samples in the fingerprint feature library,the hypothesis test and identification of abnormal security situation of IoT terminal are carried out,and finally the abnormal security situation monitoring of IoT terminal is realized.The experiment results show that the proposed method can effectively monitor the abnormal state of security situation of IoT terminal,and the mo-nitoring accuracy is higher than 85％,which fully verifies the application value of this method.
关键词
指纹特征识别/物联终端/安全态势/异常监测/假设检验Key words
fingerprint feature recognition/IoT terminal/security situation/abnormal monitoring/hypoth-esis test引用本文复制引用
出版年
2024
NETL
NSTL
万方数据