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Location Privacy-Preserving Method for Auction-Based Incentive Mechanisms in Mobile Crowd Sensing

机译:移动人群感知中基于拍卖的激励机制的位置隐私保护方法

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摘要

It is of significant importance to provide incentives to smartphone users in mobile crowd sensing systems. Recently, a number of auction-based incentive mechanisms have been proposed. However, an auction-based incentive mechanism may unexpectedly release the location privacy of smartphone users, which may seriously reduce the willingness of users participating in contributing sensing data. In an auction-based incentive mechanism, even if the location of a user is not enclosed in his/her bid submitted to the platform, the location information may still be inferred by an adversary by using the prices of the tasks required by the user. We take an example to show how an attack can recover the location information of a smartphone user by merely knowing his/her bid. To defend against such an attack, we propose a method to protect location privacy in auctions for mobile crowd sensing systems. This method encrypts prices in a bid so that the adversary cannot access and hence the location privacy of users can be protected. In the meanwhile, however, the auction can proceed properly, i.e. the platform can select the user offering the lowest price for each sensing task or the platform can choose users with budget constraint. We demonstrate the effectiveness of our proposed method with theoretical analysis and simulations.
机译:在移动人群感应系统中为智能手机用户提供激励措施非常重要。最近,已经提出了许多基于拍卖的激励机制。但是,基于拍卖的激励机制可能会意外释放智能手机用户的位置隐私,这可能会严重降低参与贡献感测数据的用户的意愿。在基于拍卖的激励机制中,即使用户的位置未包含在提交给平台的他/她的出价中,对手仍然可以通过使用用户所需任务的价格来推断位置信息。我们以一个示例来说明攻击如何仅通过了解智能手机用户的出价就可以恢复其位置信息。为了防御这种攻击,我们提出了一种在移动人群感知系统拍卖中保护位置隐私的方法。该方法对投标中的价格进行加密,以使对手无法访问,因此可以保护用户的位置隐私。但是,与此同时,拍卖可以适当地进行,即平台可以选择为每个传感任务提供最低价格的用户,或者平台可以选择有预算约束的用户。我们通过理论分析和仿真证明了我们提出的方法的有效性。

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  • 来源
    《The Computer journal》 |2018年第6期|937-948|共12页
  • 作者单位

    School of Computer Engineering and Science, Shanghai University, 99 Shangda Road, Baoshan District, Shanhai 200444, China;

    Department of Computer Science and Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Minhang District, Shanhai 200240, China;

    Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai Key Lab of Scalable Computing and Systems, 800 Dongchuan Road, Minhang District, Shanhai 200240, China;

    Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai Key Lab of Scalable Computing and Systems, 800 Dongchuan Road, Minhang District, Shanhai 200240, China;

    Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai Key Lab of Scalable Computing and Systems, 800 Dongchuan Road, Minhang District, Shanhai 200240, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
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