Collaborative Approaches to Enhancing Smart Vehicle Cybersecurity by AI-Driven Threat Detection

Fuente: arXiv
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Auteurs principaux: Ali, Syed Atif, Din, Salwa
Format: Preprint
Publié: 2024
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author Ali, Syed Atif
Din, Salwa
author_facet Ali, Syed Atif
Din, Salwa
contents The introduction sets the stage for exploring collaborative approaches to bolstering smart vehicle cybersecurity through AI-driven threat detection. As the automotive industry increasingly adopts connected and automated vehicles (CAVs), the need for robust cybersecurity measures becomes paramount. With the emergence of new vulnerabilities and security requirements, the integration of advanced technologies such as 5G networks, blockchain, and quantum computing presents promising avenues for enhancing CAV cybersecurity . Additionally, the roadmap for cybersecurity in autonomous vehicles emphasizes the importance of efficient intrusion detection systems and AI-based techniques, along with the integration of secure hardware, software stacks, and advanced threat intelligence to address cybersecurity challenges in future autonomous vehicles.
format Preprint
id arxiv_https___arxiv_org_abs_2501_00261
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Collaborative Approaches to Enhancing Smart Vehicle Cybersecurity by AI-Driven Threat Detection
Ali, Syed Atif
Din, Salwa
Cryptography and Security
Artificial Intelligence
C.2.1 Network Architecture and Design
The introduction sets the stage for exploring collaborative approaches to bolstering smart vehicle cybersecurity through AI-driven threat detection. As the automotive industry increasingly adopts connected and automated vehicles (CAVs), the need for robust cybersecurity measures becomes paramount. With the emergence of new vulnerabilities and security requirements, the integration of advanced technologies such as 5G networks, blockchain, and quantum computing presents promising avenues for enhancing CAV cybersecurity . Additionally, the roadmap for cybersecurity in autonomous vehicles emphasizes the importance of efficient intrusion detection systems and AI-based techniques, along with the integration of secure hardware, software stacks, and advanced threat intelligence to address cybersecurity challenges in future autonomous vehicles.
title Collaborative Approaches to Enhancing Smart Vehicle Cybersecurity by AI-Driven Threat Detection
topic Cryptography and Security
Artificial Intelligence
C.2.1 Network Architecture and Design
url https://arxiv.org/abs/2501.00261