System for Predicting Vulnerabilities of Industrial Control Network Based on Modified 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: 2022-06-03
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 corresponding defense measures are taken, the security of the industrial control network cannot be guaranteed.

Method used

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  • System for Predicting Vulnerabilities of Industrial Control Network Based on Modified Parameters
  • System for Predicting Vulnerabilities of Industrial Control Network Based on Modified Parameters
  • System for Predicting Vulnerabilities of Industrial Control Network Based on Modified Parameters

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0035] The computer program stored in the storage medium includes a first computer program, and when the processor executes the first computer program, the following steps are implemented:

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

[0037] Due to different P m and Q n There is a big difference in the update cycle of the model. If the sliding window is directly used to select training parameters, many parameters will not change within a certain period of time, wasting computing resources, and has little significance for model training. Therefore, in this embodiment, TP is selected. m The LCM is used as the training period port. It should be noted that, since the update period of the Internet vulnerability characteristic parameters is much larger than the update period of the industrial control network vulnerability characteristic parameters, only the update period of the Internet vu...

Embodiment 2

[0063] It should be noted that there are many Internet vulnerability characteristic parameters, which are easy to obtain. However, in some application scenarios, limited by various factors such as the scale of the industrial control network, it may not be possible to obtain enough characteristic parameters of the industrial control network to train the industrial control network. Vulnerability prediction model. However, since the trend of the outbreak of the same vulnerability in the industrial control network is consistent with the overall trend of the Internet outbreak, there is a correlation. Therefore, based on the correlation between the industrial control network and the Internet vulnerability outbreak, combined with the characteristic parameters of the Internet vulnerability, the probability of the outbreak of the industrial control network vulnerability can be calculated. predict.

[0064] Specifically, the computer program stored in the storage medium includes a secon...

Embodiment 3

[0093] The computer program stored in the storage medium includes a third computer program, and when the processor executes the third computer program, the following steps are implemented:

[0094] Step S300, obtain the text sequence {Str of each sample vulnerability id in the corresponding Summary from the database 1 ,Str 2 ,…}, Str e is the text of the Summary corresponding to the e-th update cycle, and the value of e ranges from 1 to infinity.

[0095] Step S301, when e=1, according to Str e The length of Str is determined e The feature weight w e .

[0096] Through step S301, each Str can be e Set the corresponding initial feature weights.

[0097] Step S302, when e>1, compare Str e-1 and Str e If the text information is completely consistent, then judge z*w e-1 Is it greater than the preset first feature weight threshold w emin , if greater than, set w e =z*w e-1 , where z is the preset weight adjustment coefficient, 0e-1 less than or equal to w emin , then ...

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Abstract

The present invention relates to a system for predicting loopholes in industrial control networks based on correction parameters, which implements step S201, obtaining P corresponding to each sample loophole id in a preset training period from a database. m The parameter value list, the actual outbreak probability list of Internet vulnerabilities, the actual outbreak probability list of industrial control network vulnerabilities and the true value of the industrial control network vulnerability outbreak probability; step S202, determine the correction parameter P corresponding to each sample vulnerability id CVE , to determine the corresponding training parameter value PC m , PC-based m Generate a model input vector for each sample vulnerability id; step S203, modify the parameter P according to all sample vulnerability ids CVE , training the model input vector and the true value of the vulnerability outbreak probability of the industrial control network to obtain the vulnerability prediction model of the industrial control network; step S204 , predicting the outbreak probability of the vulnerability of the industrial control network based on the vulnerability prediction model of the industrial control network. The invention can quickly and accurately predict the outbreak probability of loopholes in the industrial control network and improve the security of the industrial control network.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a system for predicting industrial control network vulnerabilities based on correction parameters. Background technique [0002] With the accelerated integration of new-generation information technologies and manufacturing technologies such as cloud computing, big data, artificial intelligence, and the Internet of Things, industrial control systems have changed from original closed and independent to open, from stand-alone to interconnected, and from automation to intelligence. While industrial enterprises have gained huge momentum for development, there have also been a lot of potential security risks. From the Stuxnet virus that targeted Iran's nuclear plant in 2010 to the Havex virus that swept Europe in 2014, the network for industrial control systems (hereinafter referred to as the industrial control network) Attacks are intensifying, and industrial control systems urgentl...

Claims

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Application Information

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Patent Type & Authority Patents(China)
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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