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Proactive Certificate Distribution for PKI in VANET

Published: 21 November 2017 Publication History

Abstract

Vehicular Ad-Hoc Networks (VANET) are the creation of several vehicles communicating with each other in order to create a network capable of communication and data exchange. One of the most promising methods for security and trust amongst vehicular networks is the usage of Public Key Infrastructure (PKI). However, current implementations of PKI as a security solution for determining the validity and authenticity of vehicles in a VANET is not efficient due to the usage of large amounts of delay and computational overhead. In this paper, we investigate the potential of PKI when predictively and preemptively passing along certificates to roadside units (RSU) in an effort to lower delay and computational overhead in a dynamic environment. We look to accomplish this through utilizing fog computing and propose a new protocol to pass certificates along the projected path.

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Cited By

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  • (2021)Intrusion Detection System for CAN Bus In-Vehicle Network based on Machine Learning Algorithms2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)10.1109/UEMCON53757.2021.9666745(0944-0949)Online publication date: 1-Dec-2021
  • (2020)Machine Learning-Based Intrusion Detection System for Controller Area NetworksProceedings of the 10th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications10.1145/3416014.3424581(41-47)Online publication date: 16-Nov-2020

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                                cover image ACM Conferences
                                Q2SWinet '17: Proceedings of the 13th ACM Symposium on QoS and Security for Wireless and Mobile Networks
                                November 2017
                                130 pages
                                ISBN:9781450351652
                                DOI:10.1145/3132114
                                Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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                                Published: 21 November 2017

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                                Author Tags

                                1. fog computing
                                2. path analysis
                                3. public-key infrastructure
                                4. smart city
                                5. vehicular ad-hoc networks

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                                View all
                                • (2021)Intrusion Detection System for CAN Bus In-Vehicle Network based on Machine Learning Algorithms2021 IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)10.1109/UEMCON53757.2021.9666745(0944-0949)Online publication date: 1-Dec-2021
                                • (2020)Machine Learning-Based Intrusion Detection System for Controller Area NetworksProceedings of the 10th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications10.1145/3416014.3424581(41-47)Online publication date: 16-Nov-2020

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