Enabling Fairness-Aware and Privacy-Preserving for Quality Evaluation in Vehicular Crowdsensing: A Decentralized Approach
With the rapid development of vehicular crowdsensing, it becomes easier and more efficient for mobile devices to sense, compute, and measure various data. However, how to address the fair quality evaluation between the platform and participants while preserving the privacy of solutions is still a ch...
Guardado en:
Autores principales: | Zhihong Wang, Yongbiao Li, Dingcheng Li, Ming Li, Bincheng Zhang, Shishi Huang, Wen He |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Hindawi-Wiley
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/7b0b86a7d2fb4343993d434a884b9c15 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
A Fair and Privacy-Preserving Image Trading System Based on Blockchain and Group Signature
por: Le Wang, et al.
Publicado: (2021) -
PARS: Privacy-Aware Reward System for Mobile Crowdsensing Systems
por: Zhong Zhang, et al.
Publicado: (2021) -
Privacy-preserving FairSwap: Fairness and privacy interplay
por: Avizheh Sepideh, et al.
Publicado: (2022) -
An Efficient and Privacy-Preserving Biometric Identification Scheme Based on the FITing-Tree
por: Xiaopeng Yang, et al.
Publicado: (2021) -
EPCT: An Efficient Privacy-Preserving and Collusion-Resisting Top-k Query Processing in WSNs
por: Qian Zhou, et al.
Publicado: (2021)