微型电脑应用

为了提升信息安全监控，加强IT多通道信息安全体系建设，提出基于物联网的IT多通道信息安全监控方法。其中物联网感知层通过融合物理方法与密码机制监控IT多通道信息采集的安全；物联网网络层利用IPv6技术监控信息传输的安全；物联网应用层利用多通道信息安全态势评估方法监控信息处理的安全；利用深度卷积神经网络提取安全态势特征，通过自适应加权的特征融合方案融合提取的特征，采用基于bagging集成的多通道-深度卷积神经网络模型获取安全态势分类结果，完成信息处理安全的监控。实验证明：该方法具有精准的IT多通道信息安全监控效果。

In order to improve the information security monitoring and strengthen the construction of IT multi-channel information security, this paper proposes a multi-channel information security monitoring method based on the Internet of Things. In the system, the perception layer of the Internet of Things monitors the security of IT multi-channel information collection through the integration of physical methods and cryptographic mechanism; the network layer of the Internet of Things uses IPv6 technology to monitor the security of information transmission; and the application layer of the Internet of Things uses multi-channel information. Information security situation assessment method is used to monitor the security of information processing; the deep convolution neural network is used to extract the security situation features, and the feature fusion scheme with adaptive weighting is used to fuse the extracted features. The multi-channel deep convolution neural network model based on bagging integration is used to obtain the security situation classification results to complete the security monitoring of information processing. Experiments show that this method has accurate IT multi-channel information security monitoring effect.