Edge Computing Enabled Anomaly Detection in IoT Environments Using Federated Learning-Reference-Cited by-同舟云学术

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Edge Computing Enabled Anomaly Detection in IoT Environments Using Federated Learning

Published:2024-05-09 Issue: Volume:12 Page:1622-1627
ISSN:
Container-title:2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE)
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Author:

Kansal Vipashi¹,Husain Saif O.²,Kumar Rakesh³,Chinthamu Narender⁴,Kumar Manish⁵,Aswini S⁶

Affiliation:

1. Graphic Era Deemed to be University,Department of Computer Science & Engineering,Dehradun

2. College of Technical Engineering, The Islamic University,Department of Computers Techniques Engineering,Najaf,Iraq

3. GLA University,Department of Computer Engineering & Applications,Mathura

4. MIT CTO,Dallas,Texas,USA

5. Lovely Professional University,Phagwara,India

6. Institute of Aeronautical Engineering,Department of Computer Science and Engineering,Hyderabad,Telangana

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10592860/10592845/10592903.pdf?arnumber=10592903

Reference37 articles.

1. Federated Learning for Intrusion Detection Systems in Internet of Vehicles: A General Taxonomy, Applications, and Future Directions

2. At the Confluence of Artificial Intelligence and Edge Computing in IoT-Based Applications: A Review and New Perspectives

3. MFGAD-INT: in-band network telemetry data-driven anomaly detection using multi-feature fusion graph deep learning

4. Botnet Detection and Mitigation Model for IoT Networks Using Federated Learning

5. A Survey of Using Machine Learning in IoT Security and the Challenges Faced by Researchers

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