Design And Implementation Of Industrial Internet Asset Detection System Based On Protocol Analysis

With the national strategies such as "made in China 2025" and"industry 4.0" put forward,the development process of industrial informatization in China has been greatly promoted.Industrial information technology has been widely used in industrial production,manufacturing,smart power grid,intelligent transportation and medical control fields,and is gradually becoming the basis of automatic production in important fields such as national industry,water conservancy,energy and transportation.However,as more and more industrial control systems are put into operation,the safety of industrial control equipment is gradually exposed.Therefore,the real time security monitoring of industrial control network becomes the primary problem.Detection is the first step of safety.There are a large number of devices running in the industrial control system.Therefore,the safety study of industrial control devices first requires the detection and discovery of industrial control devices.By studying and analyzing the shortcomings of traditional detection methods in industrial control equipment asset detection,this paper proposes an optimization method of industrial control equipment asset detection based on protocol analysis.Based on this method,an industrial Internet asset detection system based on protocol analysis is designed and implemented.Specific work includes:Firstly,through the study and comparison of the traditional Internet detection technology and the existing industrial control asset detection technology,this paper summarizes the shortcomings of the current industrial control asset detection method,such as long detection time consumption,insufficient detection feedback asset data and low detection accuracy.Secondly,the optimization method of industrial control asset exploration based on protocol analysis is designed and introduced,which mainly completes the following three aspects:1.A port exploration optimization technique based on stateless connection is proposed,which solves the problem of time resource consumption and ping suppression failure of traditional port scanning technology,improves the efficiency and accuracy of equipment port exploration,and reduces the time consumption of asset exploration.2.This paper presents a fingerprint extraction technology for industrial control equipment based on flow analysis.by designing the rules of fingerprint extraction for equipment,the fingerprint identification feature library of equipment is constructed to provide a basis for the classification detection of industrial control equipment,so as to improve the accuracy of asset detection.3.A framework of progressive asset classification detection is proposed.Based on protocol analysis,the framework firstly conducts initial asset detection for the successful equipment to obtain the initial asset data flow.Then the equipment fingerprint identification feature library is used to complete the classification and identification of industrial control equipment.Finally,based on the idea of progressive detection,incremental detection of asset information is carried out for classified equipment to improve the amount of effective data for equipment asset detection,thus solving the problem that the amount of data detected by traditional asset detection method is less.Thirdly,an industrial Internet asset detection system based on protocol analysis is designed and implemented.Based on the proposed optimization method of industrial control equipment asset detection,the system provides a front-end interface and a back-end service interface,and designs five functional modules of system management,exception handling,asset detection,asset identification and data management,which can well support the application of the proposed asset detection optimization method.Fourthly,the function and performance verification experiments of the asset detection system are designed.Experiments based on deductive and comparative methods are designed to verify the effectiveness and optimization of the system in terms of asset detection function and performance.Finally,summarize and put forward the future research direction.