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System for predicting industrial control network vulnerabilities based on bitmap

A loophole and industrial control technology, applied in the computer field, can solve problems such as the inability to guarantee the security of the industrial control network, and achieve the effects of improving accuracy and prediction efficiency, improving accuracy and training efficiency, and fast computing speed

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 corresponding defense measures are taken, the security of the industrial control network cannot be guaranteed.

Method used

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  • System for predicting industrial control network vulnerabilities based on bitmap
  • System for predicting industrial control network vulnerabilities based on bitmap
  • System for predicting industrial control network vulnerabilities based on bitmap

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, obtain 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 The update period of t is very different. If the sliding window is directly used to select the training parameters, many parameters will not change within a certain period of time, which wastes computing resources and has little significance for model training. Therefore, this embodiment selects TP m The small common multiple of is used as the training period. It should be noted that since the update period of the characteristic parameters of Internet vulnerabilities is much longer than that of the characteristic parameters of industrial control network, only the update period of characteristic parameters of Internet vul...

Embodiment 2

[0063] It should be noted that there are many characteristic parameters of Internet vulnerabilities and are easy to obtain. However, in some application scenarios, due to various factors such as the scale of the industrial control network, it may not be possible to obtain sufficient characteristic parameters of the vulnerability 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 correlation. Therefore, the outbreak probability of the industrial control network vulnerability can be calculated based on the correlation between the industrial control network and the Internet vulnerability outbreak and the characteristic parameters of the Internet vulnerability. predict.

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

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 It is the summary text corresponding to the e-th update period, and the value range of e is from 1 to infinity.

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

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

[0097] Step S302, when e>1, compare Str e-1 and Str e If the text information of is completely consistent, then judge z*w e-1 Whether it is greater than the preset first feature weight threshold w emin , if greater than, then 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 s...

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PUM

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Abstract

The invention relates to a system for predicting industrial control network vulnerabilities based on bitmap, and the method comprises the implementation steps: S501, determining a Summary cycle detection window TK based on a preset training cycle; step S502, taking Be as the a bit information in the TK, obtaining the detection window information TKe of the e period, and determining the feature weight we of Be based on the bit change in Be and TKe; step S503, on the basis of the feature weight we of each Be and the Summary text Stry, determining a Summary feature parameter value corresponding to each Summary text; and step S504, constructing a model input vector based on the Summary feature parameter value corresponding to the sample vulnerability id, training to obtain an industrial control network vulnerability prediction model, and 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 invention relates to the field of computer technology, in particular to a system for predicting loopholes in industrial control networks based on bitmaps. Background technique [0002] With the accelerated integration of cloud computing, big data, artificial intelligence, Internet of Things and other new-generation information technologies and manufacturing technologies, industrial control systems have changed from closed and independent to open, from stand-alone to interconnected, and from automation to intelligence. While industrial enterprises have gained great momentum for development, a large number of security risks have also emerged, from the Stuxnet virus targeting the Iranian nuclear plant in 2010 to the Havex virus sweeping Europe in 2014, etc., targeting industrial control system networks (hereinafter referred to as industrial control networks) Attacks are becoming more and more serious, and industrial control systems are in urgent need ...

Claims

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Application Information

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IPC IPC(8): G06F21/57
CPCG06F21/577
Inventor 李峰孙晓鹏和希文侯绪森张帅民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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