Design And Implementation Of Crowd Sensing Malicious Node Detection System Based On Block Chain

With the popularization of smart devices,crowd sensing as a new perception mode has developed rapidly.On the basis of ensuring the convenience and extensiveness of data collection,the security requirements for the perception mode of the Internet of Things are also getting higher and higher.At present,the attack methods against crowd sensing are mainly uploading illegal data through sensing nodes,such as false information uploading,black hole attack,etc.Such attacks directly affect the final data perception quality of the crowd sensing system,causing serious losses to users and the platform.Therefore,how to protect the security of the crowd-sensing system and timely detection of illegally uploaded data nodes is very important for protecting the security of the crowd-sensing system.However,the existing malicious node detection system nodes have low reliability,and the existing detection and verification methods for malicious nodes cannot achieve efficient detection in complex environments.For different applications and security requirements,this paper designs and implements a block chain-based crowd-sensing malicious node detection system.The system conducts research on the malicious behavior of malicious nodes from the aspects of node behavior and data quality to improve the detection rate of malicious nodes.This paper main research work are as follows:(1)Aiming at the problem of low credibility of detected nodes in the crowd-sensing malicious node detection system,a dual-element collaborative model of experience voting based on user behavior is designed.The model starts from the direct trust and indirect trust between nodes,and through the comprehensive evaluation of the interactive behavior of the detection nodes,it ensures the credibility of the nodes involved in the detection of malicious nodes.This model can work well in a blockchain environment due to its distributed node distribution.The experimental results show that the empirical voting dual collaborative trust model proposed in this paper can provide more accurate detection node trust value,and can provide higher data quality under the same conditions,and improve the credibility of the perception system.At the same time,the model has better robustness.(2)Aiming at the low detection rate of malicious nodes in the crowd-sensing system,a dynamic iterative detection method for malicious nodes in the crowd-sensing network based on experience voting is proposed.The dynamic iterative update in this detection method can be updated to the blockchain ledger in real time.At the same time,the mechanism evaluates the trust of the data provided by the user through the dynamically updated trust model,and handles the behavior of nodes by considering the false positive and false negative situations in the detection results.,to improve the detection rate of malicious nodes.The experimental results confirm that the design scheme in this paper can identify and isolate nodes with malicious behavior in time.Intelligent malicious node detection is supported by an adaptive trust update process in the scheme,which implicitly performs trust recovery of temporarily failed nodes and calculates different trust update factors for each node according to its behavior.At the same time,the method proposed in this paper has a higher detection rate and a lower false detection rate than other trust-based detection models,and the false detection rate only slightly changes with the increase of the number of nodes in the network.(3)Design and implement a malicious node detection system in the blockchain environment.The system deploys the trust model and detection model proposed in this study in the blockchain environment through blockchain chain code,which correspond to the evaluation module and malicious node detection module respectively.At the same time,the system uses alliance chain technology to establish a single information channel in the process of sensing data transmission,realize data isolation,protect data privacy,and improve data security.The system test shows that the malicious node detection system designed in this paper can effectively detect malicious nodes and ensure the security of the system.