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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:

LSFL: A Lightweight and Secure Federated Learning Scheme for Edge Computing
Zhuangzhuang Zhang, Libing Wu, Chuanguo Ma, et al.
IEEE Transactions on Information Forensics and Security (2022) Vol. 18, pp. 365-379
Closed Access | Times Cited: 48

Showing 1-25 of 48 citing articles:

When Federated Learning Meets Privacy-Preserving Computation
Jingxue Chen, Hang Yan, Z. Liu, et al.
ACM Computing Surveys (2024) Vol. 56, Iss. 12, pp. 1-36
Closed Access | Times Cited: 35
Federated learning for green and sustainable 6G IIoT applications
Vũ Khánh Quý, Dinh C. Nguyen, Dang Van Anh, et al.
Internet of Things (2024) Vol. 25, pp. 101061-101061
Closed Access | Times Cited: 21
Secure and efficient federated learning via novel multi-party computation and compressed sensing
Lvjun Chen, Di Xiao, Zhuyang Yu, et al.
Information Sciences (2024) Vol. 667, pp. 120481-120481
Closed Access | Times Cited: 8
ESVFL: Efficient and secure verifiable federated learning with privacy-preserving
Jiewang Cai, Wenting Shen, Jing Qin
Information Fusion (2024) Vol. 109, pp. 102420-102420
Closed Access | Times Cited: 8
Data-Agnostic Model Poisoning Against Federated Learning: A Graph Autoencoder Approach
Kai Li, Jingjing Zheng, Xin Yuan, et al.
IEEE Transactions on Information Forensics and Security (2024) Vol. 19, pp. 3465-3480
Open Access | Times Cited: 7
Small models, big impact: A review on the power of lightweight Federated Learning
Pian Qi, Diletta Chiaro, Francesco Piccialli
Future Generation Computer Systems (2024) Vol. 162, pp. 107484-107484
Open Access | Times Cited: 6
FedComm: A Privacy-Enhanced and Efficient Authentication Protocol for Federated Learning in Vehicular Ad-Hoc Networks
Xiaohan Yuan, Jiqiang Liu, Bin Wang, et al.
IEEE Transactions on Information Forensics and Security (2023) Vol. 19, pp. 777-792
Closed Access | Times Cited: 15
Privacy-Preserving Serverless Federated Learning Scheme for Internet of Things
Changti Wu, Lei Zhang, Lin Xu, et al.
IEEE Internet of Things Journal (2024) Vol. 11, Iss. 12, pp. 22429-22438
Closed Access | Times Cited: 5
Robust and Privacy-Preserving Federated Learning Scheme Based on Ciphertext-Selected Users
Xiaoming Wang, Zhiquan Liu, Huang Binrui
Computer Networks (2025), pp. 111072-111072
Closed Access
Federated Learning for Cloud and Edge Security: A Systematic Review of Challenges and AI Opportunities
Latifa Albshaier, Seetah Almarri, Abdullah Albuali
Electronics (2025) Vol. 14, Iss. 5, pp. 1019-1019
Open Access
A cutting-edge framework for industrial intrusion detection: Privacy-preserving, cost-friendly, and powered by federated learning
Lingzi Zhu, Bo Zhao, Jiabao Guo, et al.
Applied Intelligence (2025) Vol. 55, Iss. 7
Closed Access
Communication-Efficient and Byzantine-Robust Federated Learning for Mobile Edge Computing Networks
Zhuangzhuang Zhang, Libing Wu, Debiao He, et al.
IEEE Network (2023) Vol. 37, Iss. 4, pp. 112-119
Closed Access | Times Cited: 12
Efficiently Achieving Privacy Preservation and Poisoning Attack Resistance in Federated Learning
Xue-Yang Li, Xue Yang, Zhengchun Zhou, et al.
IEEE Transactions on Information Forensics and Security (2024) Vol. 19, pp. 4358-4373
Closed Access | Times Cited: 4
TICPS: A trustworthy collaborative intrusion detection framework for industrial cyber–physical systems
Lingzi Zhu, Bo Zhao, Weidong Li, et al.
Ad Hoc Networks (2024) Vol. 160, pp. 103517-103517
Closed Access | Times Cited: 4
PSFL: Ensuring Data Privacy and Model Security for Federated Learning
Jing Li, Youliang Tian, Zhou Zhou, et al.
IEEE Internet of Things Journal (2024) Vol. 11, Iss. 15, pp. 26234-26252
Closed Access | Times Cited: 4
Multiple-Round Aggregation of Abstract Semantics for Secure Heterogeneous Federated Learning
Jiao Zhang, Xiong Li, Wei Liang
Lecture notes in computer science (2025), pp. 208-227
Closed Access
Integrating CP-ABE and Device Fingerprint Into Federated Learning
Chunlu Chen, Rodrigo Román, Kevin I‐Kai Wang, et al.
Lecture notes in computer science (2025), pp. 420-436
Closed Access
More Efficient and Verifiable Privacy-Preserving Aggregation Scheme for Internet of Things-Based Federated Learning
Rongquan Shi, Lifei Wei, Lei Zhang
Applied Sciences (2024) Vol. 14, Iss. 13, pp. 5361-5361
Open Access | Times Cited: 3
Cluster-Based Secure Aggregation for Federated Learning
Jien Kim, Gunryeong Park, Miseung Kim, et al.
Electronics (2023) Vol. 12, Iss. 4, pp. 870-870
Open Access | Times Cited: 8
PA-iMFL: Communication-Efficient Privacy Amplification Method Against Data Reconstruction Attack in Improved Multilayer Federated Learning
Jianhua Wang, Xiaolin Chang, Jelena Mišić, et al.
IEEE Internet of Things Journal (2024) Vol. 11, Iss. 10, pp. 17960-17974
Open Access | Times Cited: 2
WVFL: Weighted Verifiable Secure Aggregation in Federated Learning
Yijian Zhong, Wuzheng Tan, Zhifeng Xu, et al.
IEEE Internet of Things Journal (2024) Vol. 11, Iss. 11, pp. 19926-19936
Closed Access | Times Cited: 2
Using Third-Party Auditor to Help Federated Learning: An Efficient Byzantine-robust Federated Learning
Zhuangzhuang Zhang, Libing Wu, Debiao He, et al.
IEEE Transactions on Sustainable Computing (2024) Vol. 9, Iss. 6, pp. 848-861
Closed Access | Times Cited: 2
NSPFL: A Novel Secure and Privacy-Preserving Federated Learning With Data Integrity Auditing
Zehu Zhang, Yanping Li
IEEE Transactions on Information Forensics and Security (2024) Vol. 19, pp. 4494-4506
Closed Access | Times Cited: 2
Towards Efficient Asynchronous Federated Learning in Heterogeneous Edge Environments
Yajie Zhou, Xiaoyi Pang, Zhibo Wang, et al.
IEEE INFOCOM 2022 - IEEE Conference on Computer Communications (2024), pp. 2448-2457
Closed Access | Times Cited: 2
MFLCES: Multi-Level Federated Edge Learning Algorithm Based on Client and Edge Server Selection
Zhenpeng Liu, Sichen Duan, Shuo Wang, et al.
Electronics (2023) Vol. 12, Iss. 12, pp. 2689-2689
Open Access | Times Cited: 4
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