Research On Data Analysis And Tracking Model Of Nodes Behavior In IioT Based On Blockchain

In recent years,with the deep integration of industrialization and informatization and the widespread rise of industries such as intelligent manufacturing,the Industrial Internet of Things(IIo T)has grown rapidly.There are many sensor nodes in the perception layer and are characterized by vulnerabilities of security,the issue of IIo T security is becoming a common focus in the industry;data analysis and abnormal behavior tracking of nodes behavior in IIo T based on blockchain provide a possible way to solve this problem.The main contributions of this thesis in the research on the analysis and tracking model of industrial internet node behavior data based on blockchain include:1.We propose an improved DPoS consensus mechanism for the IIo T.The IIo T node is divided into five categories,we introduce two-way supervision rules and formulate rewards and punishment mechanisms,we use the voting time difference factor to mobilize the node's enthusiasm for voting and detect malicious nodes in the consensus mechanism based on the node's credit score.Through this mechanism,the behaviors of network nodes are constrained and their respective functions are ensured.The problems in the DPoS consensus mechanism,such as low enthusiasm of node voting,joint evil among nodes in the voting cycle,and the existing DPoS consensus mechanism cannot be directly applied to the IIo T are solved.2.A block confirmation method for IIo T nodes based on blockchain is proposed.Inspired by the reviewer's right to "one vote veto",the sink node is granted the right to finally verify the legitimacy of the block,which solves the problem of lack of trust in the block confirmation process of the IIo T.3.We construct a blockchain-based detection and data tracking model for malicious nodes in the IIo T.A distributed random detection method for suspicious behavior is proposed.The behavior of the node is evaluated by monitoring the processing delay and forwarding rate of the node to ensure the reliability of the data integrity of the system.The nodes of the entire network are divided into four categories.We design a blockchainbased IIo T data blocks and smart contract solutions of malicious node detection and node data tracking.Based on distributed detection,The IIo T identifies malicious nodes and removes them from the network,ensuring the safety of the IIo T.In this thesis,OPNET simulation platform,Ethereum development framework Truffle,and local private chain simulation tool Ganache are used to conduct combined simulation of the model.The simulation results show that this method is feasible in the detection and data tracking of malicious nodes in the IIo T.The behavior analysis and tracking method of IIo T based on blockchain is helpful to improve network security.