RPTD: Reliability-enhanced Privacy-preserving Truth Discovery for Mobile Crowdsensing-Reference-Cited by-同舟云学术

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RPTD: Reliability-enhanced Privacy-preserving Truth Discovery for Mobile Crowdsensing

Published:2022-11 Issue: Volume:207 Page:103484
ISSN:1084-8045
Container-title:Journal of Network and Computer Applications
language:en
Short-container-title:Journal of Network and Computer Applications

Author:

Liu Yuxian,Liu Fagui,Wu Hao-Tian,Yang Jingfeng,Zheng Kaihong,Xu Lingling,Yan Xingfu,Hu Jiankun

Publisher

Elsevier BV

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture

Reference44 articles.

1. Abdalla, M., Catalano, D., Fiore, D., Gay, R., Ursu, B., 2018. Multi-input functional encryption for inner products: Function-hiding realizations and constructions without pairings. In: Proceedings of Annual International Cryptology Conference – CRYPTO, pp. 597–627.

2. Sdrs: A stable data-based recruitment system in IoT crowdsensing for localization tasks;Alagha;J. Netw. Comput. Appl.,2021

3. Outlier detection: Methods, models, and classification;Boukerche;ACM Comput. Surv.,2021

4. Chotard, J., Dufour Sans, E., Gay, R., Phan, D.H., Pointcheval, D., 2018. Decentralized multi-client functional encryption for inner product. In: Proceedings of Advances in Cryptology – ASIACRYPT, pp. 703–732.

5. Chotard, J., Dufour Sans, E., Gay, R., Phan, D.H., Pointcheval, D., 2018. Decentralized multi-client functional encryption for inner product. In: Proceedings of Advances in Cryptology – ASIACRYPT, pp. 703–732.

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Privacy-preserving quadratic truth discovery based on Precision partitioning;Computers & Security;2024-11

2. Boosting Crowdsourced Annotation Accuracy: Small Loss Filtering and Augmentation-Driven Training;IEEE Access;2024

3. A comprehensive survey on mobile crowdsensing systems;Journal of Systems Architecture;2023-09

4. Privacy-Preserving Truth Discovery for Collaborative-Cloud Encryption in Mobile Crowdsensing;IEEE Systems Journal;2023-09

5. Mean Field Game and Broadcast Encryption-based Joint Data Freshness Optimization and Privacy Preservation for Mobile Crowdsensing;IEEE Transactions on Vehicular Technology;2023

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