FairCs-Blockchain-Based Fair Crowdsensing Scheme using Trusted Execution Environment.
blockchain
crowdsensing
fairness
security
trusted execution environment
Journal
Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366
Informations de publication
Date de publication:
03 Jun 2020
03 Jun 2020
Historique:
received:
29
04
2020
revised:
26
05
2020
accepted:
31
05
2020
entrez:
7
6
2020
pubmed:
7
6
2020
medline:
7
6
2020
Statut:
epublish
Résumé
Crowdsensing applications provide platforms for sharing sensing data collected by mobile devices. A blockchain system has the potential to replace a traditional centralized trusted third party for crowdsensing services to perform operations that involve evaluating the quality of sensing data, finishing payment, and storing sensing data and so forth. The requirements which are codified as smart contracts are executed to evaluate the quality of sensing data in a blockchain. However, regardless of the fact that the quality of sensing data may actually be sufficient, one key challenge is that malicious requesters can deliberately publish abnormal requirements that cause failure to occur in the quality evaluation process. If requesters control a miner node or full node, they can access the data without making payment; this is because of the transparency of data stored in the blockchain. This issue promotes unfair dealing and severely lowers the motivation of workers to participate in crowdsensing tasks. We (i) propose a novel crowdsensing scheme to address this issue using Trusted Execution Environments; (ii) offer a solution for the confidentiality and integrity of sensing data, which is only accessible by the worker and corresponding requester; (iii) and finally, report on the implementation of a prototype and evaluate its performance. Our results demonstrate that the proposed solution can guarantee fairness without a significant increase in overhead.
Identifiants
pubmed: 32503191
pii: s20113172
doi: 10.3390/s20113172
pmc: PMC7309114
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : National Research Foundation of Korea
ID : NRF-2019R1A2C1090713
Références
Sensors (Basel). 2018 Nov 12;18(11):
pubmed: 30424534