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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:

Deep Anomaly Detection for Time-Series Data in Industrial IoT: A Communication-Efficient On-Device Federated Learning Approach
Yi Liu, Sahil Garg, Jiangtian Nie, et al.
IEEE Internet of Things Journal (2020) Vol. 8, Iss. 8, pp. 6348-6358
Open Access | Times Cited: 419

Showing 1-25 of 419 citing articles:

A Survey on Federated Learning for Resource-Constrained IoT Devices
Ahmed Imteaj, Urmish Thakker, Shiqiang Wang, et al.
IEEE Internet of Things Journal (2021) Vol. 9, Iss. 1, pp. 1-24
Closed Access | Times Cited: 465
Federated-Learning-Based Anomaly Detection for IoT Security Attacks
Viraaji Mothukuri, Prachi Khare, Reza M. Parizi, et al.
IEEE Internet of Things Journal (2021) Vol. 9, Iss. 4, pp. 2545-2554
Closed Access | Times Cited: 461
Industrial Internet of Things and its Applications in Industry 4.0: State of The Art
Praveen Kumar Malik, Rohit Sharma, Rajesh Singh, et al.
Computer Communications (2020) Vol. 166, pp. 125-139
Closed Access | Times Cited: 363
Privacy-preserving blockchain-based federated learning for traffic flow prediction
Yuanhang Qi, M. Shamim Hossain, Jiangtian Nie, et al.
Future Generation Computer Systems (2020) Vol. 117, pp. 328-337
Closed Access | Times Cited: 252
Deep Learning in the Industrial Internet of Things: Potentials, Challenges, and Emerging Applications
Ruhul Amin Khalil, Nasir Saeed, Mudassir Masood, et al.
IEEE Internet of Things Journal (2021) Vol. 8, Iss. 14, pp. 11016-11040
Open Access | Times Cited: 211
Secure and Provenance Enhanced Internet of Health Things Framework: A Blockchain Managed Federated Learning Approach
Md. Abdur Rahman, M. Shamim Hossain, Mohammad Saiful Islam, et al.
IEEE Access (2020) Vol. 8, pp. 205071-205087
Open Access | Times Cited: 209
Detection of False Data Injection Attacks in Smart Grid: A Secure Federated Deep Learning Approach
Yang Li, Xinhao Wei, Yuanzheng Li, et al.
IEEE Transactions on Smart Grid (2022) Vol. 13, Iss. 6, pp. 4862-4872
Open Access | Times Cited: 206
Federated Learning for Cybersecurity: Concepts, Challenges, and Future Directions
Mamoun Alazab, Swarna Priya RM, M. Parimala, et al.
IEEE Transactions on Industrial Informatics (2021) Vol. 18, Iss. 5, pp. 3501-3509
Closed Access | Times Cited: 195
Fusion of Federated Learning and Industrial Internet of Things: A survey
M. Parimala, Swarna Priya Ramu, Quoc‐Viet Pham, et al.
Computer Networks (2022) Vol. 212, pp. 109048-109048
Open Access | Times Cited: 189
Graph Neural Networks for Anomaly Detection in Industrial Internet of Things
Yulei Wu, Hong‐Ning Dai, Haina Tang
IEEE Internet of Things Journal (2021) Vol. 9, Iss. 12, pp. 9214-9231
Open Access | Times Cited: 171
Security and Privacy-Enhanced Federated Learning for Anomaly Detection in IoT Infrastructures
Lei Cui, Youyang Qu, Gang Xie, et al.
IEEE Transactions on Industrial Informatics (2021) Vol. 18, Iss. 5, pp. 3492-3500
Closed Access | Times Cited: 160
Deep Learning-Powered Vessel Trajectory Prediction for Improving Smart Traffic Services in Maritime Internet of Things
Ryan Wen Liu, Maohan Liang, Jiangtian Nie, et al.
IEEE Transactions on Network Science and Engineering (2022) Vol. 9, Iss. 5, pp. 3080-3094
Closed Access | Times Cited: 157
Deep Reinforcement Learning Assisted Federated Learning Algorithm for Data Management of IIoT
Peiying Zhang, Chao Wang, Chunxiao Jiang, et al.
IEEE Transactions on Industrial Informatics (2021) Vol. 17, Iss. 12, pp. 8475-8484
Open Access | Times Cited: 156
IoT anomaly detection methods and applications: A survey
Ayan Chatterjee, Bestoun S. Ahmed
Internet of Things (2022) Vol. 19, pp. 100568-100568
Open Access | Times Cited: 152
Toward Accurate Anomaly Detection in Industrial Internet of Things Using Hierarchical Federated Learning
Xiaoding Wang, Sahil Garg, Hui Lin, et al.
IEEE Internet of Things Journal (2021) Vol. 9, Iss. 10, pp. 7110-7119
Closed Access | Times Cited: 147
PySyft: A Library for Easy Federated Learning
Alexander Ziller, Andrew Trask, Antonio Lopardo, et al.
Studies in computational intelligence (2021), pp. 111-139
Closed Access | Times Cited: 127
Detecting cyberattacks using anomaly detection in industrial control systems: A Federated Learning approach
Trương Thu Hương, Ta Phuong Bac, Dao Minh Long, et al.
Computers in Industry (2021) Vol. 132, pp. 103509-103509
Open Access | Times Cited: 123
An ensemble deep learning model for cyber threat hunting in industrial internet of things
Abbas Yazdinejad, Mostafa Kazemi, Reza M. Parizi, et al.
Digital Communications and Networks (2022) Vol. 9, Iss. 1, pp. 101-110
Open Access | Times Cited: 116
Federated Intrusion Detection in Blockchain-Based Smart Transportation Systems
Mohamed Abdel‐Basset, Nour Moustafa, Hossam Hawash, et al.
IEEE Transactions on Intelligent Transportation Systems (2021) Vol. 23, Iss. 3, pp. 2523-2537
Closed Access | Times Cited: 113
Construction of health indicators for condition monitoring of rotating machinery: A review of the research
Haoxuan Zhou, Xin Huang, Guangrui Wen, et al.
Expert Systems with Applications (2022) Vol. 203, pp. 117297-117297
Closed Access | Times Cited: 111
Dynamic Edge Association and Resource Allocation in Self-Organizing Hierarchical Federated Learning Networks
Wei Yang Bryan Lim, Jer Shyuan Ng, Zehui Xiong, et al.
IEEE Journal on Selected Areas in Communications (2021) Vol. 39, Iss. 12, pp. 3640-3653
Open Access | Times Cited: 110
An Ensemble Multi-View Federated Learning Intrusion Detection for IoT
Dinesh Chowdary Attota, Viraaji Mothukuri, Reza M. Parizi, et al.
IEEE Access (2021) Vol. 9, pp. 117734-117745
Open Access | Times Cited: 107
Data Heterogeneity-Robust Federated Learning via Group Client Selection in Industrial IoT
Zonghang Li, Yihong He, Hongfang Yu, et al.
IEEE Internet of Things Journal (2022) Vol. 9, Iss. 18, pp. 17844-17857
Open Access | Times Cited: 94
Computing in the Sky: A Survey on Intelligent Ubiquitous Computing for UAV-Assisted 6G Networks and Industry 4.0/5.0
Saeed Hamood Alsamhi, Alexey V. Shvetsov, Santosh Kumar, et al.
Drones (2022) Vol. 6, Iss. 7, pp. 177-177
Open Access | Times Cited: 93
Energy-Efficient Federated Learning Over UAV-Enabled Wireless Powered Communications
Quoc‐Viet Pham, Mai Le, Thien Huynh‐The, et al.
IEEE Transactions on Vehicular Technology (2022) Vol. 71, Iss. 5, pp. 4977-4990
Open Access | Times Cited: 84
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