System for predicting industrial control network vulnerabilities based on correction parameters

A technology for correcting parameters and loopholes, applied in the computer field, can solve problems such as the inability to guarantee the security of industrial control networks, and achieve the effect of improving security and stability and making extensive use of value.

Active Publication Date: 2022-02-08
山东云天安全技术有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, if the outbreak of industrial control network vulnerabilities cannot be predicted in time and co

Method used

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  • System for predicting industrial control network vulnerabilities based on correction parameters
  • System for predicting industrial control network vulnerabilities based on correction parameters
  • System for predicting industrial control network vulnerabilities based on correction parameters

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0035] The computer program stored in the storage medium includes a first computer program that implements the following steps when the processor implements the first computer program:

[0036] Step S101, obtain the training cycle T of the training data set 0 = LCM (TP m ), LCM is the least common multiple function.

[0037] Due to different P m Sum n The update cycle difference is large. If you use the sliding window to select the training parameters, it will cause many parameters that do not change in a certain period of time, waste computing resources, and the model training is not significant, so this example is selected TP. m Small common multiple as the training cycle. It should be noted that since the Internet Vulnerability feature parameter update period is much larger than the industrial control network vulnerability feature parameter update period, only the Internet vulnerability feature parameter update period is considered only, which can guarantee each same vulnerabil...

Embodiment 2

[0063] It should be noted that the Internet vulnerability features are more, and it is easy to acquire, but in some application scenarios, it is limited to various factors such as industrial control network, and may not be able to obtain a sufficient amount of industrial control network vulnerability feature parameters to train the industrial control network. Vulnerability prediction model. However, due to the trend of the same loophole in the outbreak of the work control network, it is associated with the overall trend of the Internet, and therefore, the intersection of the industrial control network vulnerability explosion probability can be combined based on the associated relationship of the industrial control network and Internet vulnerability. predict.

[0064] Specifically, the computer program stored in the storage medium includes a second computer program that implements the following steps when the processor implements the second computer program:

[0065] Step S201, obt...

Embodiment 3

[0093] The computer program stored in the storage medium includes a third computer program that implements the following steps when the processor implements the third computer program:

[0094] Step S300, obtain each sample vulnerability ID from the database {STR 1 STR 2 , ...}, STR e The text of the summary corresponding to the E-update cycle, the value of E is 1 to infinity.

[0095] Step S301, when e = 1, according to STR e Length determined STR e Feature weight W e .

[0096] By step S301, it can be for each STR e Set the corresponding initial feature weight.

[0097] Step S302, when e> 1, compare Str e-1 Str e Text information, if it is exactly the same, it is judged z * w e-1 Whether it is greater than the preset first feature weight threshold W emin If it is greater than, set W e = z * w e-1 Where Z is the preset weight adjustment coefficient, 0 e-1 Less than or equal to W emin Set W e = W emin If STR e-1 Str e If the text information is inconsistent, according to STR e Len...

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Abstract

The invention relates to a system for predicting industrial control network vulnerabilities based on correction parameters, which is implemented by the following steps: S201, acquiring a parameter value list of Pm corresponding to each sample vulnerability id in a preset training period, an internet vulnerability actual outbreak probability list, an industrial control network vulnerability actual outbreak probability list and an industrial control network vulnerability outbreak probability true value from a database; s202, determining a correction parameter PCVE corresponding to each sample vulnerability id, determining a corresponding training parameter value PCm, and generating a model input vector of each sample vulnerability id based on the PCm; s203, training to obtain an industrial control network vulnerability prediction model according to the correction parameters PCVE corresponding to all the sample vulnerability id, the model input vector and the industrial control network vulnerability burst probability true value; and S204, predicting an industrial control network vulnerability outbreak probability based on the industrial control network vulnerability prediction model. According to the invention, the vulnerability outbreak probability of the industrial control network can be quickly and accurately predicted, and the safety of the industrial control network is improved.

Description

Technical field [0001] The present invention relates to computer technologies, and particularly to a system based on the correction parameter prediction industrial network vulnerability. Background technique [0002] With cloud computing, big data accelerates, artificial intelligence, networking and other new generation of information technology and manufacturing technology integration, industrial control systems from the original independently closed to an open, interconnected by a single strike from automation to intelligence. While industrial enterprises tremendous development of kinetic energy, there have been a large number of security risks, from 2010 on Iran nuclear plant Stuxnet virus, 2014 swept Europe Havex virus, for the network of industrial control system (hereinafter referred to as Control Network) attacks intensified, industrial control systems urgently need security. [0003] System vulnerabilities in industrial control systems, is an important factor affecting in...

Claims

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Application Information

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IPC IPC(8): G06F21/57
CPCG06F21/577
Inventor 李峰王绍密侯绪森时伟强宋衍龙胡建秋袁晓露王善军
Owner 山东云天安全技术有限公司
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