A Critical Analysis of Efficiency, Vulnerabilities, and Practical Limitations of AI-Driven Anomaly Detection in Modern Vehicle Systems

Harry Michaels, Morris Campbell

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DOI: 10.14293/pr2199.003990.v1
Published: 2026-06-30
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Publisher: ScienceOpen
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Cite this work

BibTeX

@article{allodium:10.14293/pr2199.003990.v1,
  title = {A Critical Analysis of Efficiency, Vulnerabilities, and Practical Limitations of AI-Driven Anomaly Detection in Modern Vehicle Systems},
  author = {Harry Michaels and Morris Campbell},
  year = {2026},
  doi = {10.14293/pr2199.003990.v1},
  url = {https://doi.org/10.14293/pr2199.003990.v1}
}

RIS

TY  - JOUR
TI  - A Critical Analysis of Efficiency, Vulnerabilities, and Practical Limitations of AI-Driven Anomaly Detection in Modern Vehicle Systems
AU  - Harry Michaels
AU  - Morris Campbell
PY  - 2026
DO  - 10.14293/pr2199.003990.v1
UR  - https://doi.org/10.14293/pr2199.003990.v1
ER  -

APA

Michaels, H., & Campbell, M. (2026). A Critical Analysis of Efficiency, Vulnerabilities, and Practical Limitations of AI-Driven Anomaly Detection in Modern Vehicle Systems. https://doi.org/10.14293/pr2199.003990.v1

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crossref · retrieved 2026-09-25T03:50:08.677Z