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  <doc>
    <id>8433</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>32</pageFirst>
    <pageLast>39</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation>IARIA</creatingCorporation>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2025-01-27</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A forensic analysis of GNSS spoofing attacks on autonomous vehicles</title>
    <abstract language="eng">Global Navigation Satellite Systems (GNSSs) are essential for modern technology, enabling precise geographic positioning in aviation, maritime shipping, and automotive systems. In the future, their role will be even more critical for autonomous vehicles, which rely on accurate localization for navigation and decision-making. However, the increasing connectivity of autonomous vehicles exposes them to cyber threats, including GNSS spoofing attacks, which manipulate location data to mislead onboard systems. As reliance on GNSS grows, so does the risk posed by spoofing attacks, making it a critical security concern. This paper describes GNSS spoofing attacks on autonomous vehicles, focusing on their detection both during and after an attack. Furthermore, we analyze data storage strategies to facilitate effective forensic analysis. We highlight the importance of position, signal, and camera data, which should be preserved to ensure a comprehensive forensic investigation. Finally, we suggest a simulation setup that enables studying which data could be used for a forensic investigation. Additionally, we examine established data frameworks and decide whether they are suitable for detecting GNSS spoofing attacks.</abstract>
    <parentTitle language="eng">Cloud Computing 2025 : The Sixteenth International Conference on Cloud Computing, GRIDs, and Virtualization, 06.-10. April 2025, Valencia</parentTitle>
    <identifier type="url">https://www.thinkmind.org/articles/cloud_computing_2025_1_50_28008.pdf</identifier>
    <identifier type="isbn">978-1-68558-258-6</identifier>
    <identifier type="issn">2308-4294</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Tobias Reichel</author>
    <author>Mathias Gerstner</author>
    <author>Leo Schiller</author>
    <author>Andreas Attenberger</author>
    <author>Rudolf Hackenberg</author>
    <author>Klara Dološ</author>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16312">Energie und Mobilität</collection>
    <collection role="oaweg" number="">Bronze Open Access - frei zugänglich aber ohne Lizenzhinweis</collection>
  </doc>
</export-example>
