Research On Perception Data Security Transmission Method Of Internet Of Things User In Mobile Edge Computing

Faced with the difficulties of privacy protection and motivating IoT(Internet of Things)users to collect perception data in the MCS(Mobile Crowd Sensing),the delay and energy consumption of perception task offloading in mobile edge computing,as well as the challenges of trusted perception data chaining in the blockchain oracle.The work of this dissertation is the research on the secure transmission method of perception data of the IoT users in mobile edge computing.The research contents and innovations in the aspects of secure collection of perception data,efficient offloading of perception data,and trusted uplink of perception data are as follows.First,in order to solve the IoT user incentive problem based on privacy protection in the MCS,an approach of flow compensation incentive based on Q-Learning strategy for privacy protection of IoT users was proposed.A strategy of local differential privacy protection based on Markov Chain Monte Carlo attribute correlation was constructed,which can generate the perceptual results with higher precision of attribute correlation.The privacy budget allocation is calculated through the privatization policy to protect the personalized privacy of perception data of IoT users.An opportunity cooperation transmission strategy of IoT user private data protection based on Q-Learning was designed to facilitate IoT user enthusiasm of participating in the perception task.Experimental test shows that the prosposed method improves the perceptual result precision by 27.06%,and declines flow compensation expenditure at 19.03% on average.Second,faced with the challenges of the high delay and energy of edge computing perception task offloading in the mobile IoT,for the offloading scenario of multi edge servers and smart devices of multi IoT users,a new method of user perception task offloading in IoT based on quantum behavior particle population optimization strategy is proposed.When the quantum behavior particle population is close to convergence,the Logistic chaos perturbation strategy is used to improve the performance of the algorithm to escape the local optimal solution.The exchange and mutation operators of the fast elite non-dominated sorting genetic algorithm based on congestion coefficient are designed,which increases the diversity of quantum particle swarm and reduces the delay and energy consumption of perception task offloading.Experimental test shows that the proposed method improves the convergence speed,delay and energy consumption of the algorithm by 4.89%,4.08% and 3.91% respectively.Third,in order to solve the problem of perception data trusted uplink in the IoT data source outside the blockchain system,a key management method of edge computing based on oracle machine for IoT user perception data trusted uplink was proposed.The key priority of IoT user smart devices and edge servers was designed to improve the connectivity of the edge center network and the performance of IoT user smart devices against capture.The optimal delineation of the tree structure acyclic graph of the mobile edge network was calculated.The edge network was divided into several sub edge networks.The smart devices of IoT users can quickly verify the smart devices of IoT users moving into the sub edge network,and can resist the dual consumption attack in the blockchain network.Experimental test shows that the proposed method reduces the calculation cost,communication cost and storage cost in the key management method.