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Mobile crowdsensing: A survey on privacy-preservation, task management, assignment models, and incentives mechanisms

机译：移动人群感知：有关隐私保护，任务管理，任务分配模型和激励机制的调查

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摘要

Mobile crowdsensing is a useful technique to collect detailed information from mobile devices of the participants. The participants need to participate to sense and transmit valuable information to the servers. Due to the technological growth, various components of mobile devices such as accelerometer, gyroscope, camera and inertial, collect vast volumes of data in a quick, efficient, and cost-effective manner. However, a mobile crowdsensing paradigm may result in serious privacy and security breaches by exposing the mobile devices to various threats and vulnerabilities. This leakage of privacy has an adverse impact on the usage and participation of mobile devices. Motivated by these threats and privacy challenges, we investigate the current approaches used for preserving privacy in mobile crowdsensing applications. After a generic description of mobile crowdsensing systems and their components, we discuss critical issues related to privacy preservation, such as task management, task assignment models, and incentive mechanisms. We also discuss various mobile crowdsensing mechanisms available in the literature. Finally, we highlight numerous research challenges that need to be addressed to improve the performance of future privacy-preserving mechanisms for mobile crowdsensing applications. (C) 2019 Elsevier B.V. All rights reserved.
机译：移动人群感知是从参与者的移动设备收集详细信息的有用技术。参与者需要参与以感知有价值的信息并将其传输到服务器。由于技术的发展，诸如加速度计，陀螺仪，照相机和惯性之类的移动设备的各种组件以快速，高效和经济高效的方式收集大量数据。但是，通过将移动设备暴露于各种威胁和漏洞，移动人群感知范例可能会导致严重的隐私和安全漏洞。隐私的泄漏对移动设备的使用和参与有不利影响。受这些威胁和隐私挑战的激励，我们研究了用于在移动人群感应应用程序中保护隐私的当前方法。在对移动式传感系统及其组件进行了一般性描述之后，我们将讨论与隐私保护相关的关键问题，例如任务管理，任务分配模型和激励机制。我们还将讨论文献中提供的各种移动人群感应机制。最后，我们重点介绍了许多研究挑战，这些挑战需要解决，以提高移动人群感应应用程序未来隐私保护机制的性能。 （C）2019 Elsevier B.V.保留所有权利。

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