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Method and device for perceiving network security situation and perceptual model training method and device

A network security and situational awareness technology, applied in the field of network security, can solve problems that trouble technicians and achieve the effect of improving versatility

Active Publication Date: 2017-07-14
GLOBAL ENERGY INTERCONNECTION RES INST CO LTD +2
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the huge amount of network data, how to perceive the network security situation based on massive data has become a difficult problem for technicians

Method used

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  • Method and device for perceiving network security situation and perceptual model training method and device
  • Method and device for perceiving network security situation and perceptual model training method and device
  • Method and device for perceiving network security situation and perceptual model training method and device

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Experimental program
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Embodiment 1

[0020] Such as figure 1 As shown, the network security situation perception model training method based on Tensorflow and Docker provided by the embodiment of the present invention is suitable for distributed systems, such as multiple linux servers connected to each other for parallel computing, including:

[0021] S1. Obtain historical network situation element data;

[0022] Specifically, network situation elements can be divided into three categories: survivability indicators, threat indicators, and vulnerability indicators. Among them, survivability indicators include network topology, network bandwidth, types and numbers of security devices, etc., and threat indicators include malicious codes. Type and quantity, number and type of alarms, data inflow, network traffic change rate, etc. Vulnerability indicators include the number of surviving hosts, the number of vulnerabilities in security devices, the number of vulnerabilities, and the number of vulnerabilities in survivi...

Embodiment 2

[0042] The embodiment of the present invention provides a network security situation awareness method based on Tensorflow and Docker, including:

[0043] Obtain the current network situation element data;

[0044] According to the element data of the current network situation, the current network situation is obtained through the preset network security situational awareness model, wherein the network security situational awareness model is trained using the network security situational awareness model training method described in Embodiment 1 and meets expectations The model for training results.

Embodiment 3

[0046] Such as figure 2 As shown, the embodiment of the present invention provides a network security situational awareness model training device based on Tensorflow and Docker, suitable for distributed systems, including:

[0047] Historical network situation element data acquisition unit 1, used to acquire the historical network situation element data;

[0048] Model training unit 2, for adopting the preset network security situational awareness model of said historical network situation element data training, said network security situational awareness model includes running in the Tensorflow width and deep learning sub-model in the Docker container;

[0049] The training result judging unit 3 is used to judge whether the training result of the network security situational awareness model meets expectations, and when the training result does not meet expectations, jump to the historical network situation element data acquisition unit.

[0050] The network security situati...

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PUM

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Abstract

The invention discloses a method and device for perceiving a network security situation based on Tensorflow and Docker and a perceptual model training method and device. The perceptual model training method comprises the following steps: acquiring historical network situation element data; adopting the historical network situation element data to train a preset network security situation perceptual model, wherein the network security situation perceptual model comprises a Tensorflow width and depth learning submodel running in a Docker container; judging whether a training result of the network security situation perceptual model achieves the expectation; and when the training result of the network security situation perceptual model does not achieve the expectation, executing the step of acquiring the historical network situation element data to the step of adopting the historical network situation element data to train the preset network security situation perceptual model repeatedly until the training result of the network security situation perceptual model achieves the expectation. Therefore, massive network data can be processed efficiently, so that the network security situation can be perceived effectively.

Description

technical field [0001] The present invention relates to the technical field of network security, in particular to a network security situation perception method and device based on Tensorflow and Docker, and a perception model training method and device. Background technique [0002] With the rapid development of information technology and network, the resource sharing of computer network is becoming more and more open and popular, and the problem of information security is becoming more and more prominent. The scope and content of network security threats are constantly expanding and evolving, and the network security situation and challenges are becoming increasingly severe and complex. Perceiving the network security situation has become a very urgent need. However, due to the huge amount of network data, how to perceive the network security situation based on massive data has become a difficult problem for technicians. Contents of the invention [0003] The technical ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L29/06G06N3/08
CPCG06N3/08H04L63/20
Inventor 张錋毛澍李彦庆张晶晶
Owner GLOBAL ENERGY INTERCONNECTION RES INST CO LTD
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