Vol. 3 No. 2 (2023): African Journal of Artificial Intelligence and Sustainable Development
Articles

Adaptive Threat Intelligence Platforms for Cybersecurity in Autonomous Vehicle Networks: Builds adaptive threat intelligence platforms tailored to the cybersecurity needs of autonomous vehicle networks

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  • Dr. Ayşe Gülcü
Dr. Ayşe Gülcü
Professor of Electrical and Electronics Engineering, Istanbul University, Turkey
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Published 14-09-2023

Keywords

  • Adaptive Threat Intelligence,
  • Cybersecurity,
  • Autonomous Vehicles
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

How to Cite

[1]
Dr. Ayşe Gülcü, “Adaptive Threat Intelligence Platforms for Cybersecurity in Autonomous Vehicle Networks: Builds adaptive threat intelligence platforms tailored to the cybersecurity needs of autonomous vehicle networks”, African J. of Artificial Int. and Sust. Dev., vol. 3, no. 2, pp. 104–113, Sep. 2023, Accessed: Dec. 03, 2024. [Online]. Available: https://africansciencegroup.com/index.php/AJAISD/article/view/77

Abstract

This paper proposes the design and implementation of adaptive threat intelligence platforms for enhancing cybersecurity in autonomous vehicle (AV) networks. The rapid advancement of AV technologies introduces new cybersecurity challenges, requiring innovative solutions to protect these vehicles from cyber threats. Traditional threat intelligence platforms are often static and unable to adapt to the dynamic nature of cyber threats faced by AVs. This paper presents a novel approach to building adaptive threat intelligence platforms that can dynamically adjust their threat detection and mitigation strategies based on real-time threat intelligence and the specific cybersecurity needs of AV networks. The proposed platforms leverage machine learning, deep learning, and other AI techniques to continuously analyze and respond to cyber threats, thereby improving the overall cybersecurity posture of AV networks.

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References

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