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Location Privacy-Preserving of Vehicular Ad-Hoc Network in Smart Cities

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The 8th International Conference on Advanced Machine Learning and Technologies and Applications (AMLTA2022) (AMLTA 2022)

Abstract

With rapid growth of technology involved in smart city networks, Nowadays, A navigation in Vehicular Ad-hoc Network (VANET) with the help of Location-Based Services (LBSs) is used to provide communications between nearby vehicles and between vehicles and fixed infrastructure on the roadside and to provide road safety, driving comfort, and infotainment. However, the privacy issues of using LBS in VANET are still challenging today. However, many LBSs run-on third-party cloud infrastructures. So, privacy is still in a huge problem. In this paper, an efficient LBS Query scheme called Privacy Preserving of Fully Homomorphic Encryption over Advanced Encryption Standard is proposed. In an encrypted manner, the LBSP’s data are outsourced to the cloud server and a registered user can get accurate LBS query results without revealing the information of location to the LBSP and cloud server provider. A real traffic scenario in Ismailia city, Egypt has been applied in the simulation. The results showed that the proposed scheme is better than the existing schemes in terms of response time, accuracy rate, and processing time.

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Correspondence to Yasmin Alkady .

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Alkady, Y., Rizk, R. (2022). Location Privacy-Preserving of Vehicular Ad-Hoc Network in Smart Cities. In: Hassanien, A.E., Rizk, R.Y., Snášel, V., Abdel-Kader, R.F. (eds) The 8th International Conference on Advanced Machine Learning and Technologies and Applications (AMLTA2022). AMLTA 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 113. Springer, Cham. https://doi.org/10.1007/978-3-031-03918-8_44

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