Abstract
In the past several decades, despite the continuous improvement of mobile devices, mobile applications requiring resources are still beyond its capacity to be completed on a single device. Due to high fairness and distribution efficiency, cloud auctions of mobile device allocation has recently attracted a lot of attention. However, most of them focus on efficiency but ignore the privacy-preserving issues in cloud auction process, which will have a significant impact on the authenticity of auctions. In this paper, we propose PAHTA, a privacy-preserving auction for heterogeneous task assignment in mobile device clouds by using Yao’s garbled circuits and homomorphic encryption. Meanwhile, we design a set of sub-protocols to support secure arithmetic operations, including secure division protocol and secure selection protocol. We further analyze the security and effectiveness of the system theoretically and prove that it can ensure sufficient and strong privacy protection under the semi-honest adversary model. Based on a large number of experiments, these results are consistent with the theoretical analysis.
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Acknowledgment
This work was partially supported by Natural Science Foundation of China (Grant No. 61602400) and Jiangsu Provincial Department of Education (Grant NO. 16KJB520043).
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Jiang, X., Pei, X., Tian, D., Li, L. (2021). Privacy-Preserving Auction for Heterogeneous Task Assignment in Mobile Device Clouds. In: Liu, Z., Wu, F., Das, S.K. (eds) Wireless Algorithms, Systems, and Applications. WASA 2021. Lecture Notes in Computer Science(), vol 12939. Springer, Cham. https://doi.org/10.1007/978-3-030-86137-7_38
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