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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:

Evaluating Federated Learning for intrusion detection in Internet of Things: Review and challenges
Enrique Mármol Campos, Pablo Fernández Saura, Aurora González-Vidal, et al.
Computer Networks (2021) Vol. 203, pp. 108661-108661
Open Access | Times Cited: 137

Showing 1-25 of 137 citing articles:

Blockchain and federated learning-based intrusion detection approaches for edge-enabled industrial IoT networks: a survey
Saqib Ali, Qianmu Li, Abdullah Yousafzai
Ad Hoc Networks (2023) Vol. 152, pp. 103320-103320
Closed Access | Times Cited: 58
Generalizing intrusion detection for heterogeneous networks: A stacked-unsupervised federated learning approach
Gustavo de Carvalho Bertoli, Lourenço Alves Pereira, Osamu Saotome, et al.
Computers & Security (2023) Vol. 127, pp. 103106-103106
Open Access | Times Cited: 48
Federated Machine Learning, Privacy-Enhancing Technologies, and Data Protection Laws in Medical Research: Scoping Review
Alissa Brauneck, Louisa Schmalhorst, Mohammad Mahdi Kazemi Majdabadi, et al.
Journal of Medical Internet Research (2023) Vol. 25, pp. e41588-e41588
Open Access | Times Cited: 43
Security of Internet of Things (IoT) using federated learning and deep learning — Recent advancements, issues and prospects
Vinay Gugueoth, Sunitha Safavat, Sachin Shetty
ICT Express (2023) Vol. 9, Iss. 5, pp. 941-960
Open Access | Times Cited: 39
Federated Learning for IoT: A Survey of Techniques, Challenges, and Applications
Ηλίας Δρίτσας, Μαρία Τρίγκα
Journal of Sensor and Actuator Networks (2025) Vol. 14, Iss. 1, pp. 9-9
Open Access | Times Cited: 2
Demystifying In-Vehicle Intrusion Detection Systems: A Survey of Surveys and a Meta-Taxonomy
Γεώργιος Καρόπουλος, Georgios Kambourakis, Efstratios Chatzoglou, et al.
Electronics (2022) Vol. 11, Iss. 7, pp. 1072-1072
Open Access | Times Cited: 50
Federated Learning for IoMT Applications: A Standardization and Benchmarking Framework of Intrusion Detection Systems
Amneh Alamleh, O. S. Albahri, A. A. Zaidan, et al.
IEEE Journal of Biomedical and Health Informatics (2022) Vol. 27, Iss. 2, pp. 878-887
Closed Access | Times Cited: 38
The role of vehicular applications in the design of future 6G infrastructures
Jorge Gallego-Madrid, Ramón Sánchez-Iborra, Jordi Ortiz, et al.
ICT Express (2023) Vol. 9, Iss. 4, pp. 556-570
Open Access | Times Cited: 21
Botnet‐based IoT network traffic analysis using deep learning
N. Joychandra Singh, Nazrul Hoque, Kh. Robindro Singh, et al.
Security and Privacy (2023) Vol. 7, Iss. 2
Closed Access | Times Cited: 21
Artificial Intelligence of Things (AIoT) for smart agriculture: A review of architectures, technologies and solutions
Dalhatu Muhammed, Ehsan Ahvar, Shohreh Ahvar, et al.
Journal of Network and Computer Applications (2024) Vol. 228, pp. 103905-103905
Open Access | Times Cited: 11
Recent endeavors in machine learning-powered intrusion detection systems for the Internet of Things
D. Manivannan
Journal of Network and Computer Applications (2024) Vol. 229, pp. 103925-103925
Closed Access | Times Cited: 8
Privacy-Aware Anomaly Detection in IoT Environments using FedGroup: A Group-Based Federated Learning Approach
Yixuan Zhang, Basem Suleiman, Muhammad Johan Alibasa, et al.
Journal of Network and Systems Management (2024) Vol. 32, Iss. 1
Open Access | Times Cited: 7
Design and Testing Novel One-Class Classifier Based on Polynomial Interpolation With Application to Networking Security
Pierpaolo Dini, Andrea Begni, Stefano Ciavarella, et al.
IEEE Access (2022) Vol. 10, pp. 67910-67924
Open Access | Times Cited: 36
The Evolution of Federated Learning-Based Intrusion Detection and Mitigation: A Survey
Léo Lavaur, Marc-Oliver Pahl, Yann Busnel, et al.
IEEE Transactions on Network and Service Management (2022) Vol. 19, Iss. 3, pp. 2309-2332
Open Access | Times Cited: 33
DeepFedWT: A federated deep learning framework for fault detection of wind turbines
Guoqian Jiang, Weipeng Fan, Wenyue Li, et al.
Measurement (2022) Vol. 199, pp. 111529-111529
Closed Access | Times Cited: 32
Comparative Review of the Intrusion Detection Systems Based on Federated Learning: Advantages and Open Challenges
Elena Fedorchenko, Evgenia Novikova, Anton Shulepov
Algorithms (2022) Vol. 15, Iss. 7, pp. 247-247
Open Access | Times Cited: 32
Federated Learning for IoT Intrusion Detection
Riccardo Lazzarini, Huaglory Tianfield, Vassilis Charissis
AI (2023) Vol. 4, Iss. 3, pp. 509-530
Open Access | Times Cited: 18
Federated learning for reliable model updates in network-based intrusion detection
Roger R. dos Santos, Eduardo K. Viegas, Altair O. Santin, et al.
Computers & Security (2023) Vol. 133, pp. 103413-103413
Closed Access | Times Cited: 17
A lightweight mini-batch federated learning approach for attack detection in IoT
Mir Shahnawaz Ahmad, Shahid Mehraj Shah
Internet of Things (2024) Vol. 25, pp. 101088-101088
Closed Access | Times Cited: 5
Misbehavior detection in intelligent transportation systems based on federated learning
Enrique Mármol Campos, José L. Hernández-Ramos, Aurora González-Vidal, et al.
Internet of Things (2024) Vol. 25, pp. 101127-101127
Open Access | Times Cited: 5
The cybersecurity mesh: A comprehensive survey of involved artificial intelligence methods, cryptographic protocols and challenges for future research
Bruno Ramos-Cruz, Javier Andreu-Pérez, Luis Martı́nez
Neurocomputing (2024) Vol. 581, pp. 127427-127427
Open Access | Times Cited: 5
A review of federated learning applications in intrusion detection systems
Aitor Belenguer, José A. Pascual, Javier Navaridas
Computer Networks (2025), pp. 111023-111023
Open Access
Asynchronous Federated Learning Based Zero Trust Architecture for the Next Generation Industrial Control Systems
Fei Lv, Hangyu Wang, Zhiwen Pan, et al.
(2025)
Closed Access
Fog-driven communication-efficient and privacy-preserving federated learning based on compressed sensing
Hui Huang, Di Xiao, Mengdi Wang, et al.
Computer Networks (2025), pp. 111043-111043
Closed Access
Advancements in training and deployment strategies for AI-based intrusion detection systems in IoT: a systematic literature review
S Kumar Reddy Mallidi, Rajeswara Rao Ramisetty
Discover Internet of Things (2025) Vol. 5, Iss. 1
Open Access
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