Dissertation/Thesis Abstract

The Vulnerabilities of Autonomous Vehicles
by Wierzynski, Amanda J., M.S., Utica College, 2019, 125; 13881137
Abstract (Summary)

The purpose of this project is to provide cybersecurity professionals and the law enforcement agencies with information on autonomous vehicles, discuss the vulnerability and exploits with recommendations for mitigating threats. The commercial,automotive manufacturers,have indicated that fully autonomous vehicles will be available to the public by 2030. The preference for autonomous vehicles supports by the anticipation of enhancing driver safety features as well as the increased mobility for the young, elderly and disabled; decrease traffic congestion, emissions, and fuel consumption. Conversely, the anticipated advantages of autonomous vehicles take precedence over the vulnerability of the network connectivity that creates the opportunity and the likelihood of cyber-attacks. The information comes from the scholarly literature on the vulnerabilities of autonomous vehicles retrieved from electronic databases. The findings reinforced the vulnerabilities within autonomous vehicles include the sensors; adaptive algorithms; and V2V, V2I, or V2X communications. The recommended techniques for decreasing the vulnerabilities include routine penetration testing, forming diligent,cooperative relationships with automotive industries concerning threats to increasing awareness while cultivating a cybersecurity culture, managing security updates, conducting digital forensic, securing information sharing, providing incident report and recovery, investing in artificial intelligence detection, and taking advantage of bug bounty programs. This project provides essential information that can be used by anyone working within the autonomous vehicle industry including cybersecurity professionals, law enforcement, policymakers, and manufacturers consulting on the mitigation of vulnerabilities in autonomous vehicles.

Indexing (document details)
Advisor: Giordano, Jaclyn V., Mullinix, Michelle D.
School: Utica College
Department: Cybersecurity
School Location: United States -- New York
Source: MAI 58/06M(E), Masters Abstracts International
Subjects: Computer science
Keywords: Autonomous vehicles, Exploits, Hacking, Incident response, Malware, Penetration testing
Publication Number: 13881137
ISBN: 978-1-392-26738-7
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