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A Novel Image-Based Homomorphic Approach for Preserving the Privacy of Autonomous Vehicles Connected to the Cloud

Sultan, A., Tahir, S., Tahir, H. , Anwer, T., Khan, F., Rajarajan, M. ORCID: 0000-0001-5814-9922 & Rana, O. F. (2022). A Novel Image-Based Homomorphic Approach for Preserving the Privacy of Autonomous Vehicles Connected to the Cloud. IEEE Transactions on Intelligent Transportation Systems, doi: 10.1109/TITS.2022.3219591

Abstract

Autonomous vehicles are taking a leap forward by performing operations without human intervention through continuous monitoring of their surroundings using multiple sensors. Images gathered through vehicle mounted cameras can be large, requiring specialized storage such as cloud. However, cloud data centres can be prone to security and privacy challenges. A partial image-based, homomorphic searchable encryption scheme is proposed, which uses pixel-level encryption to identify objects within encrypted images. The scheme provides Object-Trapdoor and Trapdoor-Image indistinguishability – as the trapdoors are probabilistic. The proposed scheme is deployed on a cloud data centre and tested over a real data set. The proposed scheme reduces storage overhead by approximately 20 times, and is 33 times more efficient compared to the generic Paillier homomorphic searchable encryption scheme. Security analysis demonstrates that the scheme maintains high levels of security and privacy.

Publication Type: Article
Additional Information: © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Publisher Keywords: Paillier homomorphic encryption, partial image encryption, Searchable Encryption
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > TL Motor vehicles. Aeronautics. Astronautics
Departments: School of Science & Technology > Engineering
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