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WheelLogger: Driver Tracing Using Smart Watch

机译:WheelLogger:使用智能手表追踪驾驶员

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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保护用户隐私的最敏感数据之一。移动设备上与位置相关的信息被盗对用户构成了严重威胁。即使在现代智能设备上对权限功能进行现成的确认可以防止信息从位置相关的传感器直接泄漏,但最近的研究表明,位置相关的信息可能通过间接的旁道攻击而泄漏。在本文中,我们展示了使用零许可智能手表应用程序无需推断用户即可推断出车辆的行驶路线。我们在实验中使用的传感器是Apple Watch上的加速度传感器。我们发现可以以83%的精度跟踪目标用户。我们建议将我们的方法用于成功攻击其他智能手机设备,因为它在Apple Watch上获得了成功,Apple Watch被认为是市场上最受限制的设备。该结果表明,如果对智能手表的零许可应用程序进行适当的操作,它可以将其转变为威胁很大的恶意软件。

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