Cited by 340Privacy-Preserving Technologies in DataBlockchain Technology Applications and SecurityCryptography and Data Security

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Privacy-preserving blockchain-based federated learning for traffic flow prediction

Qi, Yuanhang, Hossain, M. Shamim, Nie, Jiangtian, Li, Xuandi·2021·Future Generation Computer Systems

DOI 10.1016/j.future.2020.12.003

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Authors: Qi, Y., Hossain, M. S., Nie, J., & Li, X.
Affiliations: University of Electronic Science and Technology of China (CN)
King Saud University (SA)
Nanyang Technological University (SG)
Corresponding author: Hossain, M. Shamim
ORCID: Qi, Yuanhang
Hossain, M. Shamim
Nie, Jiangtian
Li, Xuandi
Venue: Future Generation Computer Systems
Publisher: Elsevier BV
Published: 2021-04
Volume: 117
Pages: 328-337
ISSN: 0167-739X (ISSN-L)
DOI: 10.1016/j.future.2020.12.003
OpenAlex: W3112885687
Cited by: 339
References: 55
Citations by year: 2026: 31 · 2025: 49 · 2024: 99 · 2023: 70 · 2022: 60 · 2021: 30
FWCI: 15.47
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
Locations: Future Generation Computer Systems (publishedVersion)
DR-NTU (Nanyang Technological University) (submittedVersion)
Funders: King Saud University, Riyadh, Saudi Arabia
Key Project in Higher Education of Guangdong Province, China (2020ZDZX3030)
Young Innovation Talents Project in Higher Education of Guangdong Province, China (2018KQNCX333)
Topics: Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
Physical Sciences › Computer Science › Computer Networks and Communications › Cryptography and Data Security
Keywords: traffic flow prediction, federated learning, blockchain, consortium blockchain, differential privacy, data poisoning, privacy preservation, intelligent transportation systems, noise addition

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