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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

A privacy-preserving and verifiable federated learning method based on blockchain
Fang Chen, Yuanbo Guo, Jiali Ma, et al.
Computer Communications (2022) Vol. 186, pp. 1-11
Closed Access | Times Cited: 35

Showing 1-25 of 35 citing articles:

Privacy-preserving in Blockchain-based Federated Learning systems
Sameera K.M., Serena Nicolazzo, Marco Arazzi, et al.
Computer Communications (2024) Vol. 222, pp. 38-67
Open Access | Times Cited: 17
Privacy-Preserving Aggregation in Federated Learning: A Survey
Ziyao Liu, Jiale Guo, Wenzhuo Yang, et al.
IEEE Transactions on Big Data (2022), pp. 1-20
Open Access | Times Cited: 51
Balancing privacy and performance in federated learning: A systematic literature review on methods and metrics
Samaneh Mohammadi, Ali Balador, Sima Sinaei, et al.
Journal of Parallel and Distributed Computing (2024) Vol. 192, pp. 104918-104918
Open Access | Times Cited: 15
SVeriFL: Successive verifiable federated learning with privacy-preserving
Hang Gao, Ningxin He, Tiegang Gao
Information Sciences (2022) Vol. 622, pp. 98-114
Closed Access | Times Cited: 36
Survey: federated learning data security and privacy-preserving in edge-Internet of Things
Haiao Li, Lina Ge, Lei Tian
Artificial Intelligence Review (2024) Vol. 57, Iss. 5
Open Access | Times Cited: 8
RFLPV: A robust federated learning scheme with privacy preservation and verifiable aggregation in IoMT
Ruyan Wang, Xingmin Yuan, Zhigang Yang, et al.
Information Fusion (2023) Vol. 102, pp. 102029-102029
Closed Access | Times Cited: 16
A systematic review of federated learning from clients’ perspective: challenges and solutions
Yashothara Shanmugarasa, Hye-Young Paik, Salil S. Kanhere, et al.
Artificial Intelligence Review (2023) Vol. 56, Iss. S2, pp. 1773-1827
Open Access | Times Cited: 14
Trustworthy Federated Learning: A Comprehensive Review, Architecture, Key Challenges, and Future Research Prospects
Asadullah Tariq, Mohamed Adel Serhani, Farag Sallabi, et al.
IEEE Open Journal of the Communications Society (2024) Vol. 5, pp. 4920-4998
Open Access | Times Cited: 4
Unlocking potential of open source model training in decentralized federated learning environment
Ekaterina Pavlova, Grigorii Melnikov, Yury Yanovich, et al.
Blockchain Research and Applications (2025), pp. 100264-100264
Open Access
EVFL-DCs: Enhancing verifiability of federated learning by double commitments based on blockchain
Qianjin Wei, Xuanjing Wu, Zhiquan Liu, et al.
Computer Networks (2025), pp. 111097-111097
Closed Access
PIN: Application-level Consensus for Blockchain-based Artificial Intelligence Frameworks
Tannishtha Devgun, Rahul Saha, Gulshan Kumar, et al.
ACM Transactions on Intelligent Systems and Technology (2025)
Open Access
A federated LSTM network for load forecasting using multi-source data with homomorphic encryption
Mengdi Wang, Rui Xin, Mingrui Xia, et al.
AIMS energy (2025) Vol. 13, Iss. 2, pp. 265-289
Open Access
A secure and efficient deep learning-based intrusion detection framework for the internet of vehicles
Hasim Ali Khan, Ghanshyam G. Tejani, Rayed AlGhamdi, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
BV-ICVs: A privacy-preserving and verifiable federated learning framework for V2X environments using blockchain and zkSNARKs
Abla Smahi, Hui Li, Yong Yang, et al.
Journal of King Saud University - Computer and Information Sciences (2023) Vol. 35, Iss. 6, pp. 101542-101542
Open Access | Times Cited: 9
Optimizing Performance in Federated Person Re-Identification through Benchmark Evaluation for Blockchain-Integrated Smart UAV Delivery Systems
Chengzu Dong, Jingwen Zhou, Qi An, et al.
Drones (2023) Vol. 7, Iss. 7, pp. 413-413
Open Access | Times Cited: 9
Blockchain-based privacy-preserving multi-tasks federated learning framework
Yunyan Jia, Ling Xiong, Yu Fan, et al.
Connection Science (2024) Vol. 36, Iss. 1
Open Access | Times Cited: 3
Blockchain consensus mechanisms comparison in fog computing: A systematic review
Yehia Ibrahim Alzoubi, Alok Mishra
ICT Express (2024) Vol. 10, Iss. 2, pp. 342-373
Open Access | Times Cited: 3
Decentralized Federated Learning: A Survey on Security and Privacy
Ehsan Hallaji, Roozbeh Razavi–Far, Mehrdad Saif, et al.
IEEE Transactions on Big Data (2024) Vol. 10, Iss. 2, pp. 194-213
Open Access | Times Cited: 2
6G optical-RF wireless integration: a review on heterogeneous cellular network channel modeling, measurements, and challenges
Mohammed Ahmed AbdlNabi, Bashar J. Hamza, Ahmad T. Abdulsadda
Telecommunication Systems (2024)
Closed Access | Times Cited: 2
Info-Chain: Reputation-Based Blockchain for Secure Information Sharing in 6G Intelligent Transportation Systems
Kun Yan, Wenping Ma, Qi Yang, et al.
IEEE Internet of Things Journal (2023) Vol. 11, Iss. 5, pp. 9198-9212
Closed Access | Times Cited: 6
VDFChain: Secure and verifiable decentralized federated learning via committee-based blockchain
Ming Zhou, Zhen Yang, Haiyang Yu, et al.
Journal of Network and Computer Applications (2023) Vol. 223, pp. 103814-103814
Closed Access | Times Cited: 6
A Review of Privacy-Preserving Federated Learning, Deep Learning, and Machine Learning IIoT and IoTs Solutions
Victor Obarafor, Man Qi, Leishi Zhang
2022 7th International Conference on Signal and Image Processing (ICSIP) (2023) Vol. 21, pp. 1074-1078
Closed Access | Times Cited: 3
Towards trustworthy federated learning: a blockchain-based architecture for auditing, traceability, and verification
Hongmin Gao, Xiaofeng Pan, Xiaojing Zhang, et al.
(2023) Vol. 16, pp. 52-52
Closed Access | Times Cited: 3
PPEFL: An Edge Federated Learning Architecture with Privacy-Preserving Mechanism
Zhenpeng Liu, Zilin Gao, Jingyi Wang, et al.
Wireless Communications and Mobile Computing (2022) Vol. 2022, pp. 1-10
Open Access | Times Cited: 5
Federify: A Verifiable Federated Learning Scheme Based on zkSNARKs and Blockchain
Ghazaleh Keshavarzkalhori, Cristina Pérez‐Solà, Guillermo Navarro‐Arribas, et al.
IEEE Access (2023) Vol. 12, pp. 3240-3255
Open Access | Times Cited: 2
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