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author:

Luo, Bin (Luo, Bin.) [1] | Li, Xinghua (Li, Xinghua.) [2] | Liu, Ximeng (Liu, Ximeng.) [3] (Scholars:刘西蒙) | Guo, Jingjing (Guo, Jingjing.) [4] | Ren, Yanbing (Ren, Yanbing.) [5] | Ma, Siqi (Ma, Siqi.) [6] | Ma, Jianfeng (Ma, Jianfeng.) [7]

Indexed by:

EI Scopus SCIE

Abstract:

When enjoying mobile crowdsensing (MCS), it is vital to evaluate the trustworthiness of mobile users (MUs) without disclosing their sensitive information. However, the existing schemes ignore this requirement in the multiple crowdsourcers (CSs) scenario. The lack of a credible sharing about MUs' trustworthiness results in an inaccurate trust evaluation, disabling allocating tasks to reliable MUs. To address it, based on the analysis of the desired properties, we propose a scheme enabling d ependable d ata collection with m ultiple crowdsourcers t rust s haring ( (DMTS)-M-2 ). Specifically, we design the MU anonymous management. Two kinds of MU generated pseudonym systems without relationships are presented to mark each MU in trust evaluation and task execution, respectively. Through the devised pseudonym changes on these pseudonyms and the common token distribution algorithm, (DMTS)-M-2 realizes privacy-preserving trust sharing. Moreover, to guarantee credible sharing, based on the hash chain, (DMTS)-M-2 records MUs' trustworthiness with the unforgeable signature on the blockchain established by multiple CSs which do not trust each other naturally. Extensive experiments show that compared with the other works, (DMTS)-M-2 's detection ratio of vicious MUs and the percentage of reliable MUs among the selected ones can increase by 208.61% and 28.27%. Both computational and communication delays are limited.

Keyword:

Blockchains data collection Games Mobile crowdsensing multiple crowdsourcers Privacy Reliability Sensors Task analysis Trust management trust sharing

Community:

  • [ 1 ] [Luo, Bin]Xidian Univ, State Key Lab Integrated Serv Networks, Xian 710071, Peoples R China
  • [ 2 ] [Li, Xinghua]Xidian Univ, State Key Lab Integrated Serv Networks, Xian 710071, Peoples R China
  • [ 3 ] [Guo, Jingjing]Xidian Univ, State Key Lab Integrated Serv Networks, Xian 710071, Peoples R China
  • [ 4 ] [Ren, Yanbing]Xidian Univ, State Key Lab Integrated Serv Networks, Xian 710071, Peoples R China
  • [ 5 ] [Ma, Jianfeng]Xidian Univ, State Key Lab Integrated Serv Networks, Xian 710071, Peoples R China
  • [ 6 ] [Luo, Bin]Xidian Univ, Sch Cyber Engn, Xian 710071, Peoples R China
  • [ 7 ] [Li, Xinghua]Xidian Univ, Sch Cyber Engn, Xian 710071, Peoples R China
  • [ 8 ] [Guo, Jingjing]Xidian Univ, Sch Cyber Engn, Xian 710071, Peoples R China
  • [ 9 ] [Ren, Yanbing]Xidian Univ, Sch Cyber Engn, Xian 710071, Peoples R China
  • [ 10 ] [Ma, Jianfeng]Xidian Univ, Sch Cyber Engn, Xian 710071, Peoples R China
  • [ 11 ] [Liu, Ximeng]Fuzhou Univ, Coll Math & Comp Sci, Fuzhou 350108, Fujian, Peoples R China
  • [ 12 ] [Ma, Siqi]Univ New South Wales, Sch Engn & Informat Technol, Sydney, NSW 2052, Australia

Reprint 's Address:

  • 刘西蒙

    [Li, Xinghua]Xidian Univ, State Key Lab Integrated Serv Networks, Xian 710071, Peoples R China;;[Li, Xinghua]Xidian Univ, Sch Cyber Engn, Xian 710071, Peoples R China;;[Liu, Ximeng]Fuzhou Univ, Coll Math & Comp Sci, Fuzhou 350108, Fujian, Peoples R China

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Source :

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

ISSN: 1041-4347

Year: 2024

Issue: 3

Volume: 36

Page: 927-942

8 . 9 0 0

JCR@2023

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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