Abstract
In traditional mobile crowdsensing (MCS) applications, the crowdsensing server (CS-server) need mobile users’ precise locations for optimal task allocation, which raises privacy concerns. This work proposes a framework P2TA to optimize task acceptance rate while protecting users’ privacy. Specifically, edge nodes are introduced as an anonymous server and a task allocation agent to prevent CS-server from directly obtaining user data and dispersing privacy risks. On this basis, a genetic algorithm that performed on edge nodes is designed to choose an initial obfuscation strategy. Furthermore, a privacy game model is used to optimize user/adversary objectives against each other to obtain a final obfuscation strategy which can be immune to posterior inference. Finally, edge nodes take user acceptance rate and task allocation rate into account comprehensively, focusing on maximizing the expected accepted task number under the constraint of differential privacy and distortion privacy. The effectiveness and superiority of P2TA to the exiting MCS task allocation schemes are validated via extensive simulations on the synthetic data, as well as the measured data collected by ourselves.
The authors gratefully acknowledge the support and financial assistance provided by the National Natural Science Foundation of China under Grant Nos. 61502230, 61501224 and 61073197, the Natural Science Foundation of Jiangsu Province under Grant No. BK20150960, the Natural Science Foundation of the Jiangsu Higher Education Institutions of China under Grant No. 15KJB520015, and Nangjing Municipal Science and Technology Plan Project under Grant No. 201608009.
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Hu, Y., Shen, H., Bai, G., Wang, T. (2018). Privacy-Preserving Task Allocation for Edge Computing Enhanced Mobile Crowdsensing. In: Vaidya, J., Li, J. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2018. Lecture Notes in Computer Science(), vol 11337. Springer, Cham. https://doi.org/10.1007/978-3-030-05063-4_33
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DOI: https://doi.org/10.1007/978-3-030-05063-4_33
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