Design And Implementation Of Vulnerability Analysis System For Industrial Networked Equipment

Along with the rapid development of modern industrial intelligence,the closed mode of traditional industrial systems has gradually evolved into openness,which has promoted the development of production while also introduced non-negligible security risks for the use of industrial equipment.Therefore,in order to discover security threats to industrial systems in advance,reduce or avoid damage and impact on industrial enterprises due to vulnerability exploitation,and establish a perfect advanced protection system,the research work is mainly carried out from three aspects: industrial control equipment level identification,vulnerability attribute analysis and prediction,and vulnerability hazard assessment,as follows:Firstly,this paper analyzes and studies the network hierarchy of industrial control equipment for the problem of existing equipment identification technology with high volatility in industrial networking environment,and extracts feature fields from the interaction data to form a device feature fingerprint,as the basis for subsequent research on the improvement of the clustering recognition algorithm.And then industrial equipment hierarchy recognition technology is explored,based on optimized clustering recognition algorithm,to meet the business needs of industrial control multi-networked equipment identification tools run while ensuring accuracy,stability and timeliness.Secondly,this paper establishes a template for discriminating vulnerability attack effectiveness and risk category attributes,while defin-ing multi-angle evaluation indicators for the degree of risk hazards,in order to solve the problem of delayed generic scoring of vulnerabilities and to enable timely and effective comprehensive evaluation of the risk of industrial control vulnerabilities.An automated prediction model of risk level based on ernie Cat is proposed,which uses the fusion features described in this paper of vulnerabilities as well as the intrinsic evaluation attributes of vulnerabilities to obtain prediction results of the overall threat level of industrial vulnerabilities.An automated risk level prediction model based on ernie Cat is proposed,which uses the fusion features of vulnerability text descriptions as well as intrinsic evaluation attributes of vulnerabilities to obtain prediction results for the overall threat level of industrial vulnerabilities.Thirdly,in order to achieve a comprehensive elemental analysis of industrial control vulnerability hazards,this paper combines device-level critical information with vulnerability-level risk situations,establishes multi-perspective quantitative evaluation indicators to quantitatively assess the risk hazard level for device vulnerabilities,and prioritizes the threat level based on the overall rating of the output hazard level.Finally,a vulnerability analysis system for industrial networked devices is designed and implemented based on the above research.The system achieves comprehensive analysis and assessment of industrial control vulnerabilities by obtaining asset-level information as well as the results of vulnerability risk categories and harm level predictions.