Operation risk assessment method and device based on network security situation awareness system
A situational awareness and network security technology, applied in the field of power system security, can solve the problems of limited accuracy of evaluation models, inability to quantify system security status, limited applicability of online applications, etc., to improve accuracy and comprehensiveness. Effect
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no. 1 example
[0051] see Figure 1-3 .
[0052] like figure 1 As shown, this embodiment provides an operational risk assessment method based on a network security situational awareness system, which at least includes the following steps:
[0053] S1. Pre-collect historical data of the network security situational awareness system and analyze and process it;
[0054] In a preferred embodiment, the network security situation awareness system includes a system host, a switch, a router device, a vertical secret authentication device, a forward isolation device and a firewall device.
[0055] Specifically, for step S1, the power monitoring system includes a plurality of network security devices and components, and the state data collected and analyzed mainly from the general system host in the present invention include: login information, key file change information, USB access information, CPU usage information , memory usage information, disk usage information, network port status informati...
no. 2 example
[0110] see Figure 4 .
[0111] Such as Figure 4 As shown, this embodiment provides an operational risk assessment device based on a network security situational awareness system, including:
[0112] The data collection module 100 is used to pre-collect historical data of the network security situational awareness system and analyze and process it;
[0113] The data processing module 200 is used to perform feature selection and data preprocessing on the historical data of the network security situational awareness system, and generate a training set and a test set for training the learning model;
[0114] Model training module 300, is used for according to described training set and test set, adopts machine learning algorithm to complete the training of learning model, calculates the average accuracy rate of learning model recognition, and derives the intelligent analysis model that satisfies the accuracy rate condition;
[0115] The model prediction module 400 is used to ...
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