Cybersecurity Threats in Connected and Automated Vehicles based Federated Learning Systems-Reference-Cited by-同舟云学术

Cybersecurity Threats in Connected and Automated Vehicles based Federated Learning Systems

Published:2021-07-11 Issue: Volume: Page:
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Container-title:2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops)
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Author:

Al Mallah Ranwa,Badu-Marfo Godwin,Farooq Bilal

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9669138/9669201/09669214.pdf?arnumber=9669214

Reference13 articles.

1. Towards federated learning at scale: System design;bonawitz;arXiv preprint arXiv 1902 11152,2019

2. Deep learning based anticipatory multi-objective eco-routing strategies for connected and automated vehicles;alfaseeh;arXiv preprint arXiv 2006 13823,2020

3. Distributed dynamic routing using network of intelligent intersections;djavadian;ITS Canada ACGM,2018

4. A Performance Evaluation of Federated Learning Algorithms

5. Danger ahead: The government’s plan for vehicle-to-vehicle communication threatens privacy, security, and common sense;williams,2017

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