Research on the Quality Assessment and Protection of Network Security Body Based on Intelligent Induction and Deep Learning

This mechanism mainly saves the induction information in the distributed cloud storage node, and saves the message summary of the induction information in the block chain node, and then the corresponding relationship between the cloud storage node and the block chain node is saved in the induction information management machine. When the user reads the data, the identity authentication is first completed at the induction information management machine, and the induction information is obtained through the key, and finally the data verification is completed at the block chain node. The main advantages of this mechanism are: using block chain to store intelligent sensing information, and using chain storage to reduce the cost of storage, thus enhancing the scalability of block chain storage. This mechanism uses new hash chains to transmit inductive information, thus improving the security of transmission. Through this study proposes an access control strategy for intelligent sensing information. In this way, the user with the key can quickly complete the work certificate and complete the access, while the illegal intruder who does not hold the key cannot calculate the work certificate of the next block based on the existing block, so he cannot access the intelligence. Under the network topology set in this paper, the model with step 2 is significantly better than step 1 and 3, with 18.30% and 75.01% reduction on MAPE and 15.66% and 87.79% reduction on RMSE. Through hidden Markov, the security situation of the information system under the time series is determined. Through SSIPN, the security event is not used as a single situation assessment index, but the network topology and node vulnerability are included in the assessment scope to enhance the correlation between the security event and each node in the information system. Based on SSIPN, the weight allocation algorithm of the corresponding nodes is proposed, which accurately reflects the impact of the level of the nodes on the network on the overall situation, and realizes the security situation assessment of the overall network.