Cross-layer Federated Heterogeneous Ensemble Learning for Lightweight IoT Intrusion Detection System-Reference-Cited by-同舟云学术

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Cross-layer Federated Heterogeneous Ensemble Learning for Lightweight IoT Intrusion Detection System

Published:2023-10-09 Issue: Volume: Page:
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Container-title:2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA)
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Author:

Hajj Suzan¹,Azar Joseph²,Abdo Jacques Bou³,Demerjian Jacques⁴,Makhoul Abdallah²,Ginhac Dominique¹

Affiliation:

1. Université de Bourgogne Franche-Comté,ImViA,Dijon,France,21078

2. Femto-St Institute, UMR 6174 CNRS, Université de Franche-Comté,France

3. University of Cincinnati,School of Information Technology,Cincinnati,OH,USA,45221

4. Lebanese University,LaRRIS, Faculty of Sciences,Fanar,Lebanon

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10302431/10302461/10302497.pdf?arnumber=10302497

Reference50 articles.

1. Recent Advances on Federated Learning for Cybersecurity and Cybersecurity for Federated Learning for Internet of Things

2. Federated Learning for intrusion detection system: Concepts, challenges and future directions

3. A Critical Review on the Implementation of Static Data Sampling Techniques to Detect Network Attacks

4. A survey on iot intrusion detection: Federated learning, game theory, social psychology and explainable ai as future directions;arisdakessian;IEEE Internet of Things Journal,2022

5. A review of federated learning in intrusion detection systems for iot;belenguer;arXiv preprint arXiv 2204 12443,2022

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