"Applications of Encrypted AI in Autonomous Vehicles"
Keywords:
Autonomous vehicles, Encrypted AI, Privacy-preserving AI, Data security, Homomorphic encryptionAbstract
Autonomous vehicles (AVs) represent a transformative technology poised to revolutionize transportation by enhancing safety, efficiency, and convenience. Central to their development is the integration of Artificial Intelligence (AI) systems capable of processing vast amounts of data in real-time. However, the deployment of AI in AVs raises significant concerns regarding data security and privacy. Encrypted AI techniques emerge as a crucial solution to mitigate these risks while enabling advanced functionalities in autonomous driving. This abstract explores the applications of encrypted AI in autonomous vehicles, focusing on its role in safeguarding sensitive data, ensuring secure communications, and preserving user privacy. Encrypted AI facilitates secure model training and inference processes by encrypting data at rest and in transit, thereby preventing unauthorized access and tampering. Moreover, it enables collaborative learning among multiple vehicles without compromising individual data privacy.
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Copyright (c) 2023 International Journal of Business Management and Visuals, ISSN: 3006-2705
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.