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

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。

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 proposed.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 feature 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 monitoring accuracy is higher than 85%,which fully verifies the application value of this method.