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A decentralised approach to privacy preserving trajectory mining

机译:一种去中心化的隐私保护轨迹挖掘方法

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摘要

Large volumes of mobility data is collected in various application domains. Enterprise applications are designed on the notion of centralised data control where the proprietary of the data rests with the enterprise and not with the user. This has consequences as evident by the occasional privacy breaches. Trajectory mining is an important data mining problem, however, trajectory data can disclose sensitive location information about users. In this work, we propose a decentralised blockchain-enabled privacy-preserving trajectory data mining framework where the proprietary of the data rests with the user and not with the enterprise. We formalise the privacy preservation in trajectory data mining settings, present a proposal for privacy preservation, and implement the solution as a proof-of-concept. A comprehensive experimental evaluation is conducted to assess the applicability of the system. The results show that the proposed system yields promising results for blockchain-enabled privacy preservation in user trajectory data. (C) 2019 Elsevier B.V. All rights reserved.
机译:在各种应用程序域中收集了大量的移动性数据。企业应用程序是基于集中式数据控制的概念设计的,其中数据的专有权属于企业而不是用户。从偶尔的隐私泄露中可以看出其后果。轨迹挖掘是一个重要的数据挖掘问题,但是,轨迹数据可以泄露有关用户的敏感位置信息。在这项工作中,我们提出了一个去中心化的,启用区块链的隐私保护轨迹数据挖掘框架,其中数据的专有权属于用户而不是企业。我们在轨迹数据挖掘设置中正式确定了隐私保护,提出了隐私保护提案,并将该解决方案作为概念验证来实施。进行了全面的实验评估,以评估系统的适用性。结果表明,所提出的系统对于在用户轨迹数据中启用区块链的隐私保护产生了可喜的结果。 (C)2019 Elsevier B.V.保留所有权利。

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