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

Privacy-Preserving Data Analytics for IoT-enabled Autonomous Vehicles - Challenges and Solutions: Discusses challenges and solutions in implementing privacy-preserving data analytics for IoT-enabled Avs

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  • Dr. Peter Murphy
Dr. Peter Murphy
Professor of Computer Science, Dublin City University, Ireland
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Published 14-09-2023

Keywords

  • Privacy,
  • Data Analytics,
  • IoT
Creative Commons License

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

How to Cite

[1]
Dr. Peter Murphy, “Privacy-Preserving Data Analytics for IoT-enabled Autonomous Vehicles - Challenges and Solutions: Discusses challenges and solutions in implementing privacy-preserving data analytics for IoT-enabled Avs”, African J. of Artificial Int. and Sust. Dev., vol. 3, no. 2, pp. 39–47, Sep. 2023, Accessed: Dec. 22, 2024. [Online]. Available: https://africansciencegroup.com/index.php/AJAISD/article/view/70

Abstract

Autonomous vehicles (AVs) represent a significant advancement in transportation technology, promising improved safety, efficiency, and convenience. However, the extensive use of IoT devices in AVs raises concerns about data privacy and security. This paper explores the challenges associated with implementing privacy-preserving data analytics for IoT-enabled AVs and proposes solutions to address these challenges. The key challenges include data anonymization, secure data sharing, and ensuring compliance with regulations such as GDPR. Solutions include the use of encryption techniques, blockchain technology, and differential privacy. By addressing these challenges, it is possible to enhance the privacy and security of IoT-enabled AVs, making them safer and more reliable for widespread adoption.

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References

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