Asynchronous Federated Learning for Intrusion Detection in Vehicular Cyber-Physical Systems
Author:
Affiliation:
1. Howard University,Department of Electrical Engineering and Computer Science,Washington,DC,USA,20059
Funder
U.S. Army Research Laboratory
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10225747/10225748/10225917.pdf?arnumber=10225917
Reference19 articles.
1. Investigation on Deep Learning Methods for Privacy and Security Challenges of Cognitive IoV
2. Vehicular Cyber Physical Systems
3. Internet of vehicles (iov): evolution, architecture, security issues and trust aspects;Indu;Int J Recent Technol Eng (IJRTE),2019
4. Implementing blockchain technology in the Internet of Vehicle (IoV)
5. Blockchain-Based Internet of Vehicles (IoV): An Efficient Secure Ad Hoc Vehicular Networking Architecture
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1. An equilibrium optimizer with deep recurrent neural networks enabled intrusion detection in secure cyber-physical systems;AIMS Mathematics;2024
2. Optimal Asynchronous Federated Learning for the Internet of Battlefield Things (IoBT);2023 International Conference on Machine Learning and Applications (ICMLA);2023-12-15
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