Computer Science ›› 2022, Vol. 49 ›› Issue (5): 303-310.doi: 10.11896/jsjkx.210400077

• Information Security • Previous Articles     Next Articles

Review of Privacy-preserving Mechanisms in Crowdsensing

LI Li1, HE Xin2,3, HAN Zhi-jie3   

  1. 1 School of Computer and Information Engineering,Henan University,Kaifeng,Henan 475004,China
    2 International Joint Laboratory of Intelligent Network Theory and Key Technology,Henan University,Kaifeng,Henan 475004,China
    3 School of Software,Henan University,Kaifeng,Henan 475004,China
  • Received:2021-04-08 Revised:2021-07-20 Online:2022-05-15 Published:2022-05-06
  • About author:LI Li,born in 1977,Ph.D candidate, is a student member of China Computer Federation.Her main research interests include crowdcomputing,crowdsensing,privacy-preserving and machine lear-ning.
    HE Xin,born in 1974,professor,Ph.D supervisor,is a senior member of China Computer Federation.His main research interests include crowdsensing,mobilecomputing,cloudcomputing and big data processing.
  • Supported by:
    National Natural Science Foundation of China(61672209,61701170),Major Science and Technology Special Project of Henan Province(201300210400) and Key R & D and Promotion Special Project of Henan Province(212102210094).

Abstract: In recent years,the rapid popularity of intelligent terminals has greatly promoted the development of crowdsensing service paradigm,which integrates data collection,analysis and processing.As a necessary base to ensure the safe operation of services and encourage the participation of sensing users,privacy-preserving has become the primary issue to be solved.This paper presents the state-of-the-art in privacy-preserving mechanisms for crowdsensing service.After describing its main components,this paper discusses the definition and metrics of privacy-preserving from the view of crowdsensing’s whole life cycle.The privacy-preserving mechanisms designed in literatures are analyzed and discussed according to different stages in crowdsensing’s whole-life-cycle,and the experimental datasets used in literatures are given.Finally,Future research challenges are proposed based on the development of crowdsensing and global regulatory requirements for privacy-preserving.

Key words: Anonymization, Crowdcomputing, Crowdsensing, Encryption, Privacy-preserving

CLC Number: 

  • TP393
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