Privacy-preserving QoI-aware participant coordination for mobile crowdsourcing
Privacy-preserving QoI-aware participant coordination for mobile crowdsourcing
复制标题
移动众包的隐私保护、QoI 感知参与者协调
DOI：
10.1016/j.comnet.2015.12.022
复制
发表时间：
2016-06
影响因子：
5.6
通讯作者：
Wang, Wendong
中科院分区：
文献类型：
--
作者：
Song, Zheng;Ren, Ziyu;Ma, Jian;Wang, Wendong
移动的众包系统是物联网（IoT）的重要信息源，诸如通过雇用普通公民参与数据收集来收集用于各种应用的位置相关感测数据。为了提高收集数据的信息质量（Quality of Information，QoI），系统服务器需要协调具有不同数据收集能力和各种激励要求的参与者。然而，现有的参与者协调方法要求参与者向系统服务器透露他们的轨迹，这导致隐私泄漏。但是，随着普通公民维权意识的提高，隐私泄露的风险可能会降低他们收集数据的积极性。在本文中，我们提出了一个参与者协调框架，它允许系统服务器提供最佳的QoI传感任务，而不知道参与者的轨迹。参与者协同工作，协调他们的传感任务，而不是依赖于传统的集中式服务器。进一步提出了一种合作数据聚合、激励分配方法和惩罚机制，以保护参与者隐私并确保收集数据的QoI。仿真结果表明，该方法可以有效地选择合适的参与者，以实现更好的QoI比其他方法，并能有效地保护每个参与者的隐私。
Mobile crowdsourcing systems are important sources of information for the Internet of Things (IoT) such as gathering location related sensing data for various applications by employing ordinary citizens to participate in data collection. In order to improve the Quality of Information (QoI) of the collected data, the system server needs to coordinate participants with different data collection capabilities and various incentive requirements. However, existing participant coordination methods require the participants to reveal their trajectories to the system server which causes privacy leakage. But, with the improvement of ordinary citizens’ consciousness to protect their rights, the risk of privacy leakage may reduce their enthusiasm for data collection. In this paper, we propose a participant coordination framework, which allows the system server to provide optimal QoI for sensing tasks without knowing the trajectories of participants. The participants work cooperatively to coordinate their sensing tasks instead of relying on the traditional centralized server. A cooperative data aggregation, an incentive distribution method, and a punishment mechanism are further proposed to both protect participant privacy and ensure the QoI of the collected data. Simulation results show that our proposed method can efficiently select appropriate participants to achieve better QoI than other methods, and can protect each participant’s privacy effectively.
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影响因子：
6.4
作者：
Chen, Min;Gonzalez, Sergio;Leung, Victor C. M.
通讯作者：
Leung, Victor C. M.
DOI：
10.1145/1460412.1460440
发表时间：
2008-11
期刊：
--
影响因子：
--
作者：
R. Ganti;N. Pham;Yu-En Tsai;T. Abdelzaher
通讯作者：
R. Ganti;N. Pham;Yu-En Tsai;T. Abdelzaher
DOI：
10.15783/c7qc7m
发表时间：
2014-07
期刊：
CRAWDAD wireless network data archive
影响因子：
--
作者：
L. Bracciale;Marc Bonola;Pierpaolo Loreti;G. Bianchi;R. Amici;Antonello Rabuffi
通讯作者：
L. Bracciale;Marc Bonola;Pierpaolo Loreti;G. Bianchi;R. Amici;Antonello Rabuffi
DOI：
10.1109/infcom.2012.6195541
发表时间：
2012-03
期刊：
2012 Proceedings IEEE INFOCOM
影响因子：
--
作者：
Lingjie Duan;T. Kubo;Kohei Sugiyama;Jianwei Huang;T. Hasegawa;J. Walrand
通讯作者：
Lingjie Duan;T. Kubo;Kohei Sugiyama;Jianwei Huang;T. Hasegawa;J. Walrand
影响因子：
11.2
作者：
Cardone, Giuseppe;Cirri, Andrea;Foschini, Luca
通讯作者：
Foschini, Luca