Challenges and future directions of secure federated learning: a survey

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A Hierarchical Federated Learning Algorithm Based on Time Aggregation in Edge Computing Environment

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FedMDO: Privacy-Preserving Federated Learning via Mixup Differential Objective

You, X., Liu, C., Li, J., Sun, Y., & Liu, X. (2024) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2024.3408463 · Cited by 17 · see citing works

High-Fidelity Gradient Inversion in Distributed Learning

Ye, Z., Luo, W., Zhou, Q., & Tang, Y. (2024) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v38i18.29975 · Cited by 16 · see citing works

IDS-DWKAFL: An intrusion detection scheme based on Dynamic Weighted K-asynchronous Federated Learning for smart grid

Wen, M., Zhang, Y., Zhang, P., & Chen, L. (2025) · Journal of Information Security and Applications · doi:10.1016/j.jisa.2025.103993 · Cited by 15 · see citing works

A Blockchain-based federated learning framework for secure aggregation and fair incentives

Yang, X., & Li, T. (2024) · Connection Science · doi:10.1080/09540091.2024.2316018 · Cited by 15 · see citing works

Accuracy Degrading: Toward Participation-Fair Federated Learning

You, X., Liu, X., Lin, X., Cai, J., & Chen, S. (2023) · IEEE Internet of Things Journal · doi:10.1109/jiot.2023.3238038 · Cited by 15 · see citing works

SecureLLM: A Unified Framework for Privacy-Focused Large Language Models

Kalodanis, K., Papadopoulos, S., Feretzakis, G., Rizomiliotis, P., & Anagnostopoulos, D. (2025) · Applied Sciences · doi:10.3390/app15084180 · Cited by 14 · see citing works

Quality of service‐aware adaptive radio resource management based on deep federated Q‐learning for multi‐access edge computing in beyond 5G cloud‐radio access network

Kumar, N., & Ahmad, A. (2023) · Transactions on Emerging Telecommunications Technologies · doi:10.1002/ett.4762 · Cited by 13 · see citing works

Blockchain Empowered Federated Learning for Distributed Network Security Behaviour Knowledge Base in 6G

Li, K., Zhou, H., Tu, Z., Liu, F., & Zhang, H. (2022) · Security and Communication Networks · doi:10.1155/2022/4233238 · Cited by 14 · see citing works

F-CBR: An Architecture for Federated Case-Based Reasoning

Jaiswal, A. D., Yigzaw, K. Y., & Öztürk, P. (2022) · IEEE Access · doi:10.1109/access.2022.3188808 · Cited by 12 · see citing works

Optimized Active Fuzzy Deep Federated Learning for predicting autism spectrum disorder

Daliri, A., Khalilian, M., Mohammadzadeh, J., & Hosseini, S. S. (2025) · Network Modeling Analysis in Health Informatics and Bioinformatics · doi:10.1007/s13721-025-00523-3 · Cited by 11 · see citing works

Against network attacks in renewable power plants: Malicious behavior defense for federated learning

Wu, X., Jin, Z., Zhou, J., Liu, K., & Liu, Z. (2024) · Computer Networks · doi:10.1016/j.comnet.2024.110577 · Cited by 10 · see citing works

A Comprehensive Survey on Split-Fed Learning: Methods, Innovations, and Future Directions

Hukkeri, G. S., Goudar, R. H., Dhananjaya, G. M., Rathod, V. N., & Ankalaki, S. (2025) · IEEE Access · doi:10.1109/access.2025.3547641 · Cited by 10 · see citing works

Future of the Medical World: Collaborative Medical Imaging AI With Federated Learning

Rahmaniar, W., Deng, Z., Yang, Y., Jin, Z., & Suzuki, K. (2025) · IEEE Consumer Electronics Magazine · doi:10.1109/mce.2025.3539474 · Cited by 9 · see citing works

Enhancing Scalability and Reliability in Semi-Decentralized Federated Learning With Blockchain: Trust Penalization and Asynchronous Functionality

Shrestha, A. K., Khan, F. A., Shaikh, M. A., Jaberzadeh, A., & Geng, J. (2023) · IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) · doi:10.1109/uemcon59035.2023.10316006 · Cited by 9 · see citing works

Sequential POI Recommend Based on Personalized Federated Learning

Dong, Q., Liu, B., Zhang, X., Qin, J., & Wang, B. (2023) · Neural Processing Letters · doi:10.1007/s11063-023-11264-7 · Cited by 9 · see citing works

Privacy-preserving federated discovery of DNA motifs with differential privacy

Chen, Y., Gan, W., Huang, G., Wu, Y., & Yu, P. S. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.123799 · Cited by 8 · see citing works

Privacy-Preserving Large-Scale AI Models for Intelligent Railway Transportation Systems: Hierarchical Poisoning Attacks and Defenses in Federated Learning

Zhu, Y., Chong, L., Chen, C., Lyu, X., Chen, Z., Wang, B., Hu, F., Li, H., Dai, J., Cai, B., et al. (2024) · Computer Modeling in Engineering & Sciences · doi:10.32604/cmes.2024.054820 · Cited by 7 · see citing works

Federated Learning for Industry 5.0: A State-of-the-Art Review

Ramírez-Gordillo, T., Calabuig-Barbero, E., Mora, H., Pujol, F. A., & Amador, S. (2023) · Lecture notes in networks and systems · doi:10.1007/978-3-031-48590-9_6 · Cited by 7 · see citing works

Institutional Acceleration

Allen, D. W. E., Berg, C., & Potts, J. (2025) · Cambridge University Press eBooks · doi:10.1017/9781009638616 · Cited by 3 · see citing works

Federated Learning: Attacks and Defenses, Rewards, Energy Efficiency: Past, Present and Future

Karydas, D., & Leligou, H. C. (2024) · WSEAS Transactions on Computers archive · doi:10.37394/23205.2024.23.10 · Cited by 6 · see citing works

Collaborative Edge-Cloud AI for IoT Driven Secure Healthcare System

Gupta, L. (2023) · IEEE International Systems Conference (SysCon) · doi:10.1109/syscon53073.2023.10131082 · Cited by 6 · see citing works

Federated Multi-Label Learning (FMLL): Innovative Method for Classification Tasks in Animal Science

Ghasemkhani, B., Varlıklar, Ö., Doğan, Y., Utku, S., Birant, K. U., & Birant, D. (2024) · Animals · doi:10.3390/ani14142021 · Cited by 6 · see citing works

SecureFed: A Two-Phase Framework for Detecting Malicious Clients in Federated Learning

Likhitha, A., Mhatre, A., Nair, A. K., & Gupta, D. (2025) · IEEE International Conference on Information Reuse and Integration (IRI) · doi:10.1109/iri66576.2025.00043 · Cited by 6 · see citing works

Evolutionary Neural Architecture Search and Its Applications in Healthcare

Liu, X., Li, J., Zhao, J., Cao, B., Yan, R., & Lv, Z. (2023) · Computer Modeling in Engineering & Sciences · doi:10.32604/cmes.2023.030391 · Cited by 6 · see citing works

Protecting health monitoring privacy in fitness training: A federated learning framework based on personalized differential privacy

Shao, L. (2024) · Internet Technology Letters · doi:10.1002/itl2.499 · Cited by 5 · see citing works

Privacy preservation using optimized Federated Learning: A critical survey

Narule, Y. S., & Thakre, K. S. (2024) · Intelligent Decision Technologies · doi:10.3233/idt-230104 · Cited by 5 · see citing works

Performance Evaluation of Distance-Statistical Based Byzantine-Robust Algorithms in Federated Learning

Colosimo, F., & Rango, F. D. (2024) · IEEE Wireless Communications and Networking Conference · doi:10.1109/wcnc57260.2024.10570891 · Cited by 5 · see citing works

Linkage on security, privacy and fairness in federated learning: New balances and new perspectives

Wang, L., Zhu, T., Zhou, W., & Yu, P. S. (2025) · Neural Networks · doi:10.1016/j.neunet.2025.107874 · Cited by 8 · see citing works

FedDistillSC: A Distributed Semantic Communication System Based on Federated Distillation

Xing, H., Ma, H., Xiao, Z., Zhao, B., Peng, J., Luo, S., Feng, L., & Xu, L. (2023) · IEEE International Conference on Communication Technology (ICCT) · doi:10.1109/icct59356.2023.10419624 · Cited by 5 · see citing works

A Security-Oriented Overview of Federated Learning Utilizing Layered Reference Model

Lu, J., Fukumoto, N., & Nakao, A. (2024) · IEEE Access · doi:10.1109/access.2024.3404948 · Cited by 5 · see citing works

A privacy-centric federated learning framework with blockchain and dynamic client selection mechanisms

Saidi, A. A., Amira, A., & Nouali, O. (2025) · Cluster Computing · doi:10.1007/s10586-025-05715-0 · Cited by 4 · see citing works

Clinical AI in Radiology: Foundations, Trends, Applications, and Emerging Directions

Hartsock, I., Koutsoubis, N., Ahmed, S., Parker, N. H., Schabath, M. B., Araujo, C. R., Qayyum, A., Lam, C. A., Gatenby, R. A., & Rasool, G. (2026) · Cancers · doi:10.3390/cancers18060942 · Cited by 4 · see citing works

Dynamic Clustering Federated Learning for Non-IID Data

Chen, M., Wu, J., Yin, Y., Huang, Z., Liu, Q., & Chen, E. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-20503-3_10 · Cited by 4 · see citing works

Federated Learning in Data Privacy and Security

Reddy, D. T., Nandigam, H., Indla, S. C., & Raja, S. P. (2024) · ADCAIJ ADVANCES IN DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE JOURNAL · doi:10.14201/adcaij.31647 · Cited by 4 · see citing works

Label synchronization strategies for hybrid federated learning

Rosero, R. L., Silva, C., Ribeiro, B., Albisser, M., Brutsche, M., & Chao, M. A. (2024) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2024.110751 · Cited by 4 · see citing works

FDeep: A Fog-based Intrusion Detection System for Smart Home using Deep Learning

Gazdar, T. (2022) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2022.0131242 · Cited by 4 · see citing works

A Multiscale Recursive Attention Gate Federation Method for Multiple Working Conditions Fault Diagnosis

Zhang, Z., Zhou, F., Wang, C., Wen, C., Hu, X., & Wang, T. (2023) · Entropy · doi:10.3390/e25081165 · Cited by 4 · see citing works

The Influence of Labour Legislation on Job Creation and Job Sustainability in South Africa

Womack, C. A. J. (2021) · doi:10.4102/aosis.2020.bk238 · Cited by 4 · see citing works

A hybrid graph neural network-based federated learning method for personalized manufacturing service composition recommendation

Wang, L., Li, T., Xu, Y., Xiang, F., Zhang, X., & Zuo, Y. N. (2025) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2025.2461022 · Cited by 3 · see citing works

A Federated Learning Architecture for Bird Species Classification in Wetlands

Mulero-Pérez, D., Rodriguez-Juan, J., Ramírez-Gordillo, T., Benavent-Lledó, M., Ruiz-Ponce, P., Ortiz-Pérez, D., Hernandez-Lopez, H., Iarovikov, A., García‐Rodríguez, J., Sebastián‐González, E., et al. (2025) · Journal of Sensor and Actuator Networks · doi:10.3390/jsan14040071 · Cited by 3 · see citing works

A correlation analysis-based federated learning framework for defending against collusion-free-riding attacks

Xue, M., Zhong, H., Shi, Y., Zeng, Y., Zhang, J., & Zhao, N. (2025) · Cybersecurity · doi:10.1186/s42400-025-00366-5 · Cited by 3 · see citing works

Value allocation mechanism for multi-agent data sharing in digital innovation network: Agent-based modeling

Fan, R., Yang, L., Liu, D., & Hu, W. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.130124 · Cited by 3 · see citing works

Technical considerations of federated learning in digital healthcare systems

Alozie, E., Olagunju, H. I., Faruk, N., & Garba, S. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-13897-3.00009-6 · Cited by 3 · see citing works

Federated Feature Concatenate Method for Heterogeneous Computing in Federated Learning

Chung, W., Chang, Y.-C., Hsu, C., Chang, C., & Hung, C. (2023) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2023.035720 · Cited by 3 · see citing works

Efficient and Trustworthy Federated Learning-Based Explainable Anomaly Detection: Challenges, Methods, and Future Directions

Ha, D. T., Bac, T. P., Tran, K. D., & Tran, K. P. (2023) · Springer series in reliability engineering · doi:10.1007/978-3-031-30510-8_8 · Cited by 3 · see citing works

CustomFair: A Customized Fairness Method for Federated Recommender Systems in Social Internet of Things

Chen, G., Li, C., Du, F., Yuan, X., Chi, C., Yin, Z., Wang, B., Li, T., Bao, X., & Wang, W. (2024) · IEEE Internet of Things Journal · doi:10.1109/jiot.2024.3482703 · Cited by 2 · see citing works

Federated Learning for Secure and Privacy-Preserving Medical Collaboration Across Multi-Cloud Healthcare Systems

Ejaz, U., Islam, S. A. M., Sarkar, A., & Imashev, A. (2024) · IOSR Journal of Mechanical and Civil Engineering · doi:10.9790/1684-2105023644 · Cited by 2 · see citing works

IPCADP‐Equalizer: An Improved Multibalance Privacy Preservation Scheme against Backdoor Attacks in Federated Learning

Lian, W., Zhang, Y., Chen, X., Jia, B., & Zhang, X. (2023) · International Journal of Intelligent Systems · doi:10.1155/2023/6357750 · Cited by 2 · see citing works

An innovative technological infrastructure for managing SARS-CoV-2 data across different cohorts in compliance with General Data Protection Regulation

Dellacasa, C. M., Ortali, M., Rossi, E., Attieh, H. A., Osmo, T., Puskaric, M., Rinaldi, E., Praßer, F., Stellmach, C., Cataudella, S., et al. (2024) · Digital Health · doi:10.1177/20552076241248922 · Cited by 2 · see citing works

Enhancing Security for Smart Ehealthcare System based on Federated Learning and Homomorphic Encryption

Nguyen-Khanh, D., Huynh-Phu, L., Phan-Trung, K., Nguyen-Khanh, T., & Le‐Trung, Q. (2024) · International Conference on Advanced Computing and Analytics (ACOMPA) · doi:10.1109/acompa64883.2024.00026 · Cited by 2 · see citing works

Federated Learning for Credit Scoring Model Using Blockchain

Djolev, D., Lazarova, M. K., & Nakov, O. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-53025-8_8 · Cited by 2 · see citing works

A trusted decision fusion approach for the power internet of things with federated learning

Li, W., Zhang, N., Liu, Z., Ma, S., Ke, H., Wang, J., & Chen, T. (2023) · Frontiers in Energy Research · doi:10.3389/fenrg.2023.1061779 · Cited by 1 · see citing works

A federated learning-based approach for land surface temperature prediction considering cost-efficiency in seasonally frozen ground region

Lu, Y., Mei, G., Yang, Y., & Ding, H. (2024) · Georisk Assessment and Management of Risk for Engineered Systems and Geohazards · doi:10.1080/17499518.2024.2337384 · Cited by 1 · see citing works

Towards practical data alignment in production federated learning

Shi, Y., Yu, W., Zhang, Y., Xue, C., Zeng, Y., Zhou, Z., Guo, M., Xin, L., & Nie, W. (2024) · Frontiers of Computer Science · doi:10.1007/s11704-024-3936-0 · Cited by 1 · see citing works

Efficient Privacy-Preserving Threshold Private Set Intersection in Cross-Domain Federated Learning Data Alignment

Zhou, S., Chen, L., Wang, Y., Yang, X., & Yuan, K. (2025) · IEEE Internet of Things Journal · doi:10.1109/jiot.2025.3620818 · Cited by 1 · see citing works

Blockchain-based federated learning with metric and imbalanced learning for visual classification

Wu, F., Lu, J., Jin, H., Song, Y., Gao, G., & Jing, X. (2026) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2026.110961 · Cited by 1 · see citing works

A review of federated learning: architectures, challenges, and targeted solutions

Velaei, M., Ghahramani, H., Ghaffari, A., & Derakhshanfard, N. (2026) · Cluster Computing · doi:10.1007/s10586-026-06286-4 · Cited by 1 · see citing works

Communication-efficient federated learning for edge IoT via combined quantization and sparsification

Malik, S., Grag, A., & Kansal, N. (2026) · Discover Electronics · doi:10.1007/s44291-026-00278-9 · Cited by 1 · see citing works

Mobile health‐empowered traditional ethnic sports: AI‐based data analysis improving security

Liu, N., & Jin, Y. (2023) · Internet Technology Letters · doi:10.1002/itl2.417 · Cited by 1 · see citing works

Empowering Biomedical Health with Federated Learning: Addressing Privacy and Data Sharing for Enhanced Disease Detection and Diagnosis

Raheem, A., Zhen, Y., Yu, H., Sabah, F., Ahmed, S., & Yaqub, M. (2023) · IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC) · doi:10.1109/ic-nidc59918.2023.10388495 · Cited by 1 · see citing works

Byzantine-Robust Federated Learning Based on Dynamic Gradient Filtering

Colosimo, F., & Rango, F. D. (2024) · International Wireless Communications and Mobile Computing Conference (IWCMC) · doi:10.1109/iwcmc61514.2024.10592438 · Cited by 1 · see citing works

Candidate Models for Federated Learning with Blockchain

Tao, W., & Yin, Q. (2022) · IEEE International Conference on Big Data Analytics (ICBDA) · doi:10.1109/icbda55095.2022.9760330 · Cited by 1 · see citing works

Introduction to Federated Learning

Yu, S., & Cui, L. (2022) · Digital Privacy and Security · doi:10.1007/978-981-19-8692-5_1 · Cited by 1 · see citing works

Gradient Information from Google GBoard NWP LSTM is Sufficient to Reconstruct Words Typed

Suliman, M., & Leith, D. J. (2022) · Cyber Research Conference - Ireland (Cyber-RCI) · doi:10.1109/cyber-rci55324.2022.10032666

Mobile Keyword Prediction using Federated Learning

Chouhan, K. U., Jha, N. P. K., Jha, R. S., Kamaluddin, S. I., & Giri, N. (2023) · International Journal for Research in Applied Science and Engineering Technology · doi:10.22214/ijraset.2023.50826

From distributed machine learning to federated learning: In the view of data privacy and security

Shen, S., Zhu, T., Wu, D., Wang, W., & Zhou, W. (2020) · Concurrency and Computation Practice and Experience · doi:10.1002/cpe.6002 · Cited by 128 · see citing works

Privacy-Preservation for Federated Learning: Survey and Future Directions

Saraswat, D., Mali, T., Verma, A., & Gautam, S. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-79041-6_25

On the security and privacy of federated learning: A survey with attacks, defenses, frameworks, applications, and future directions

Jimenez-Gutierrez, D. M., Falkouskaya, Y., Hernández-Ramos, J. L., Anagnostopoulos, A., Chatzigiannakis, I., & Vitaletti, A. (2026) · Information Fusion · doi:10.1016/j.inffus.2026.104155 · Cited by 26 · see citing works

Achieving security and privacy in federated learning systems: Survey, research challenges and future directions

Blanco-Justicia, A., Domingo‐Ferrer, J., Mart́ınez, S., Sánchez, D., Flanagan, A., & Tan, K. E. (2021) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2021.104468 · Cited by 169 · see citing works

Research Progress on Security and Privacy of Federated Learning: A Survey

Ma, X., & Yan, M. (2024) · Wireless Personal Communications · doi:10.1007/s11277-024-11372-0 · Cited by 3 · see citing works