Abstract
In the Vehicular Ad-hoc Networks (VANETs), a vehicle or the vehicle driver could be perceived and followed by listening in its inquiries (e.g., reference points) by an enemy, since these quires contain individual data and information, for example, the questions and area of the vehicle. This attack prompts dangers on the vehicles area protection. The current arrangements, practices anonymizer, a Third Trusted Party (TTP) in the middle of the LBS and the vehicles. The addition of the TTP shifts the imperilled element from the LBS to the Anonymizer, with respect to security hazard, and with the endangered anonymizer, the vehicles or vehicles drivers related information will likewise be in danger. In this paper, we think of productive area based correspondence protection in VANETs communication. In which, we utilize the Fog Computing (FC) alongside TTP calculation and data perturbation. Before sending the inquiry to the TTP first we anonymizes the communication information by utilizing data perturbation. Then, we utilize the Adaptive Interval Cloaking Algorithm (AICA) as TTP to handle the ideal question from vehicles to LBS. In this paper, we provide the double communication privacy based on data perturbations and AICA. Subsequent to accepting the prepared inquiry from the LBS, the TTP sends the outcomes back to the drives, where the vehicle drivers finds their ideal results. The results shows that the proposed method save the security area dependent on the questions at the low correspondence and computational expense.
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Acknowledgments
This work was supported in part by the National Natural Science Foundation of China under Grant 61632009 and Grant 61872097, in part by the Guangdong Provincial Natural Science Foundation under Grant 2017A030308006, and in part by the High-Level Talents Program of Higher Education in Guangdong Province under Grant 2016ZJ01.
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Arif, M., Chen, J., Liu, P., Wang, G. (2021). Location Based Communication Privacy in Internet of Vehicles Using Fog Computing. In: Wang, G., Chen, B., Li, W., Di Pietro, R., Yan, X., Han, H. (eds) Security, Privacy, and Anonymity in Computation, Communication, and Storage. SpaCCS 2020. Lecture Notes in Computer Science(), vol 12383. Springer, Cham. https://doi.org/10.1007/978-3-030-68884-4_7
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