Federated Learning-based Architecture for Detecting Position Spoofing in Basic Safety Messages-Reference-Cited by-同舟云学术

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Federated Learning-based Architecture for Detecting Position Spoofing in Basic Safety Messages

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring)
language:
Short-container-title:

Author:

Bonfim Kenniston Arraes¹,Dutra Fernando Da Silva¹,Siqueira Carlos Eduardo Travagini¹,Meneguette Rodolfo Ipolito²,Dos Santos Aldri Luiz³,Júnior Lourenço Alves Pereira¹

Affiliation:

1. Aeronautics Institute of Technology,Division of Computer Science,São Paulo,Brazil

2. University of Sao Paulo (USP),Institute of Math and Computer Science,São Paulo,Brazil

3. Federal University of Minas Gerais,Department of Computer Science,Belo Horizonte,Brazil

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10199114/10199145/10199980.pdf?arnumber=10199980

Reference16 articles.

1. Communication-efficient learning of deep networks from decentralized data;mcmahan;Artificial Intelligence and Statistics,2017

2. Misbehavior Detection using Machine Learning in Vehicular Communication Networks

3. Generalizing intrusion detection for heterogeneous networks: A stacked-unsupervised federated learning approach

4. Physical layer plausibility checks for misbehavior detection in V2X networks

5. DISMISS-BSM: an Architecture for Detecting Position Spoofing in Basic Safety Messages

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