Privacy-preserving verifiable data aggregation and analysis for cloud-assisted mobile crowdsourcing
Privacy-preserving verifiable data aggregation and analysis for cloud-assisted mobile crowdsourcing
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DOI：
10.1109/infocom.2016.7524547
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发表时间：
2016-04
期刊：
影响因子：
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通讯作者：
Gaoqiang Zhuo;Qi Jia;Linke Guo;Ming Li;Pan Li
中科院分区：
文献类型：
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作者：
Gaoqiang Zhuo;Qi Jia;Linke Guo;Ming Li;Pan Li
众包是一种基于人群的外包，请求者（任务所有者）可以将任务外包给工人（公共人群）。最近，移动的众包（crowdsourcing）引起了广泛关注，该众包可以利用来自智能手机的工人数据进行数据聚合和分析。然而，当数据量变得很大时，请求者聚合和分析传入的数据成为一个难题，特别是当请求者是普通智能手机用户或存储和计算资源有限的初创公司时。此外，工人们担心他们的身份和数据隐私。为了解决这些问题，我们引入了一个三方架构的移动的众包，其中的云之间的工人和请求者实现，以减轻存储和计算负担的资源有限的请求者。还实现了身份隐私和数据隐私。使用我们的方案，请求者能够验证来自云的计算结果的正确性。我们还在工作中提供了一些汇总统计数据，以及有效的数据更新方法。大量的仿真结果表明，我们提出的解决方案的可行性和效率。
Crowdsourcing is a crowd-based outsourcing, where a requester (task owner) can outsource tasks to workers (public crowd). Recently, mobile crowdsourcing, which can leverage workers' data from smartphones for data aggregation and analysis, has attracted much attention. However, when the data volume is getting large, it becomes a difficult problem for a requester to aggregate and analyze the incoming data, especially when the requester is an ordinary smartphone user or a start-up company with limited storage and computation resources. Besides, workers are concerned about their identity and data privacy. To tackle these issues, we introduce a three-party architecture for mobile crowdsourcing, where the cloud is implemented between workers and requesters to ease the storage and computation burden of the resource-limited requester. Identity privacy and data privacy are also achieved. With our scheme, a requester is able to verify the correctness of computation results from the cloud. We also provide several aggregated statistics in our work, together with efficient data update methods. Extensive simulation shows both the feasibility and efficiency of our proposed solution.