Tracking the Human Mobility Using Mobile Device Sensors
Tracking the Human Mobility Using Mobile Device Sensors
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DOI：
10.1587/transinf.2016icp0022
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发表时间：
2017-08
期刊：
影响因子：
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通讯作者：
Takuya Watanabe;Mitsuaki Akiyama;Tatsuya Mori
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文献类型：
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作者：
Takuya Watanabe;Mitsuaki Akiyama;Tatsuya Mori
我们开发了一种新颖的概念验证侧通道攻击框架，称为 RouteDetector，它通过简单地读取智能设备传感器（加速度计、磁力计和陀螺仪）来识别火车旅行的路线。所有这些传感器都被许多应用程序广泛使用，无需任何权限。 RouteDetector的关键技术组件可以概括如下。首先，通过将机器学习技术应用于从传感器收集的数据，RouteDetector 检测用户的活动，即“行走”、“在移动的车辆中”或“其他”。接下来，它从检测到的人类活动序列中提取车辆的出发/到达时间。最后，通过将检测到的车辆出发/到达时间与从骑手所在国家/地区所有铁路公司收集的时刻表/路线图相关联，它可以识别可用于行程的潜在路线。我们通过现场实验和使用 172 家铁路公司 9,090 个火车站的时刻表和路线图进行的广泛模拟实验，证明了该策略的可行性。关键词: 移动安全, 侧信道攻击, 位置识别
We developed a novel, proof-of-concept side-channel attack framework called RouteDetector, which identifies a route for a train trip by simply reading smart device sensors: an accelerometer, magnetometer, and gyroscope. All these sensors are commonly used by many apps without requiring any permissions. The key technical components of RouteDetector can be summarized as follows. First, by applying a machine-learning technique to the data collected from sensors, RouteDetector detects the activity of a user, i.e., “walking,” “in moving vehicle,” or “other.” Next, it extracts departure/arrival times of vehicles from the sequence of the detected human activities. Finally, by correlating the detected departure/arrival times of the vehicle with timetables/route maps collected from all the railway companies in the rider’s country, it identifies potential routes that can be used for a trip. We demonstrate that the strategy is feasible through field experiments and extensive simulation experiments using timetables and route maps for 9,090 railway stations of 172 railway companies. key words: mobile security, side-channel attack, location identification