| With the wide application of smart devices and the rapid development of network technology,the crowd sensing system has become an important means to collect sensory data on a large scale.As an effective technology to extract real information from the unreliable data,truth discovery technology is an important tool to solve this problem.However,sensory data may carry sensitive information of users,and upload data directly will bring risks of privacy disclosure to users.To ensure the information security of users,it is of great significance to add privacy protection technology into the truth discovery scheme.At present,some privacy-preserving truth discovery schemes have been proposed,but there are still privacy and efficiency problems.In order to solve these problems,this thesis studies the incremental truth discovery algorithms of privacy protection in crowd sensing system.The main contributions of this thesis are as follows:(1)In this thesis,a new privacy-preserving scheme is designed by combining symmetric encryption technology and incremental truth discovery technology to solve the problem of privacy-preserving truth discovery in crowd sensing under the application scenario of continuous collection of sensory data.The scheme is based on a single cloud server.In the process of truth discovery,a homomorphic encryption algorithm with lower complexity is used to reduce the computational and communication costs of users and cloud servers.(2)In order to further improve the efficiency of the privacy-preserving incremental truth discovery algorithm,this thesis also designs an incremental truth discovery scheme under the dual cloud server model.This scheme adopts an efficient public key homomorphic encryption algorithm,which further reduces the computation and communication overhead of the whole truth discovery process while protecting users' private information.The results of simulation experiments verify the high efficiency of these schemes. |
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