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WheelLogger: Driver Tracing Using Smart Watch

机译:wheellogger:使用智能手表驾驶员跟踪

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Location-related data is one of the most sensitive data for user privacy. Theft of location-related information on mobile device poses serious threats to users. Even though the extant confirmation of permissions feature on modern smart devices can prevent direct leakage of information from location-related sensors, recent research has shown that leakage of location-related information is possible through indirect, side-channel attacks. In this paper, we show that the travel path of a vehicle can be inferred without acknowledging the user using a zero-permission smart watch application. The sensor we used in our experiment is the accelerometer sensor on Apple Watch. We find that a targeted user can be traced with 83% accuracy. We suggest that our approach may be used to successfully attack other smart phone devices because it was successful on Apple Watch, which is considered as the most constrained device in the market. This result shows that the zero-permission application on a smart watch, if manipulated adequately, can transform into a high-threat malware.
机译:与位置相关的数据是用户隐私最敏感的数据之一。有关移动设备的位置相关信息的盗窃对用户构成了严重威胁。尽管现代智能设备上的许可证特征的现存确认可以防止信息与与地点相关的传感器的信息直接泄漏,但最近的研究表明,通过间接,侧通道攻击可以泄漏位置相关信息。在本文中,我们表明,可以使用零权限智能手表应用程序在不承认用户的情况下推断出车辆的行驶路径。我们在我们的实验中使用的传感器是Apple Watch上的加速度计传感器。我们发现目标用户可以追溯到83%的精度。我们建议我们的方法可用于成功攻击其他智能手机设备,因为它在Apple Watch成功,这被认为是市场中最受约束的设备。此结果表明,如果充分操纵,则智能手表上的零权限应用程序可以转换为高威胁恶意软件。

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