L3P-DLI:针对无线人群感应系统的双层激励轻量级定位-隐私保护方案

Jing Bai;Jinsong Gui;Neal N. Xiong;Anfeng Liu;Jie Wu
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摘要

移动人群传感(MCS)作为一种前景广阔的传感模式,主要依靠无线通信网络和广泛分布的移动工作人员来捕捉周围环境的数据。然而,大多数移动人群感知任务的定位依赖性往往要求工作人员在报告中嵌入自己的定位,这可能会导致隐私泄露和参与热情下降。考虑到工人对定位隐私的不同看法,我们在本文中提出了双层激励的轻量级定位隐私保护方案(L3P-DLI),以高效、低成本的方式满足工人的个性化隐私要求,同时激发他们的参与热情。据我们所知,该方案首次尝试使用代理转发来保护工人的敏感定位,同时确保高质量的传感结果。此外,我们还精心设计了双层激励机制,以激励工人积极参与或担任代理。具体来说,数据收集者和代理人之间的双向拍卖可以保障数据收集者的安全,并弥补代理人帮助转发数据可能造成的隐私泄露成本。此外,反向拍卖机制还能让平台奖励被招募的工人,以补偿他们的各种成本。在真实数据集上进行的大量实验验证了 L3P-DLI 能够有效保护工人的定位隐私,同时最大限度地提高他们的收入,以鼓励他们参与。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
L3P-DLI: A Lightweight Positioning-Privacy Protection Scheme With Double-Layer Incentives for Wireless Crowd Sensing Systems
Mobile Crowd Sensing (MCS), as a promising sensing paradigm, significantly relies on wireless communication networks and widely distributed mobile workers to capture data from the surroundings. However, the positioning-dependent nature of most MCS tasks often requires workers to embed their positionings in reports, which may result in privacy leakage and a decline in their participation enthusiasm. Considering workers’ diverse perceptions of positioning privacy, in this paper we propose the Lightweight Positioning-Privacy Protection Scheme with Double-Layer Incentives (L3P-DLI) to meet their personalized privacy requirements in an efficient and low-cost way while stimulating their participation. To the best of our knowledge, this scheme is the first attempt to employ proxy forwarding to protect workers’ sensitive positionings while ensuring high-quality sensing results. Moreover, our double-layer incentivizing mechanism is elaborately designed to motivate workers to actively participate or serve as proxies. Specifically, the bidirectional auction between data collectors and proxies can safeguard the security of data collectors, and compensate for the potential privacy leakage cost of proxies helping to forward data. Additionally, the reverse auction mechanism enables the platform to reward recruited workers to compensate for their various costs. Extensive experiments conducted on real-world datasets validate that L3P-DLI effectively preserves workers’ positioning privacy while maximizing their income to encourage participation.
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