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• W4313446997 abstract "Mobile crowdsensing recruits a group of users and utilizes their sensing devices to accomplish the sensing task. It can offer a flexible and scalable sensing paradigm with low deploying costs. As the development of vehicle networks, many works in the literature have investigated how to use vehicles as the sensing units for mobile crowdsensing. However, the majority of these works suffer some limitations. First, they can either achieve privacy preserving or supervision, but not both. Second, they mainly consider a single sensing task and overlook the management of users’ reputations across multiple tasks. To address these limitations, we propose a multi-task mobile crowdsensing scheme with conditional privacy preserving for vehicle networks. In our proposed scheme, the privacy preserving requirement and the supervision requirement can be harmonized, achieving a property called conditional privacy preserving. Moreover, each vehicle can participate in multiple sensing tasks at the same time. Specifically, privacy protection covers identity privacy, location privacy and reputation privacy simultaneously. And the reputation center does not need to store any internal information (e.g. random numbers or ephemeral keys) when updating the vehicles’ pseudonyms, reducing the risks of Denial-of-Service (DoS) attacks. Therefore, it provides a more secure and practical solution for mobile crowdsensing. Security analyses prove that our scheme achieves the desirable security requirements, such as correctness, conditional privacy preserving and authentication. And efficiency analyses demonstrate that our scheme can be used efficiently in multi-task mobile crowdsensing." @default.
• W4313446997 created "2023-01-06" @default.
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• W4313446997 date "2022-01-01" @default.
• W4313446997 modified "2023-10-16" @default.
• W4313446997 title "A Multi-task Mobile Crowdsensing Scheme with Conditional Privacy Preserving for Vehicle Networks" @default.
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• W4313446997 doi "https://doi.org/10.1007/978-3-031-23098-1_2" @default.
• W4313446997 hasPublicationYear "2022" @default.
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