Precise Wireless Camera Localization Leveraging Traffic-Aided Spatial Analysis
Precise Wireless Camera Localization Leveraging Traffic-Aided Spatial Analysis
复制标题
DOI：
10.1109/tmc.2023.3333272
复制
发表时间：
2024-06
影响因子：
7.9
通讯作者：
Yan He;Qiuye He;Song Fang;Yao Liu
中科院分区：
文献类型：
--
作者：
Yan He;Qiuye He;Song Fang;Yao Liu
如今的无线摄像头通常使用运动传感器来识别他们的视野中正在发生的事情，然后开始记录并通知财产所有者活动。在本文中，我们发现运动感知动作可以通过一种新的无线摄像机定位技术MotionCompass来揭示摄像机的位置。通过创建运动刺激并嗅探无线流量以响应该刺激，用户可以获得运动检测区域内的运动轨迹，然后使用它们来计算摄像机的位置。我们还扩展了摄像机定位算法以精确定位始终活动模式下的摄像机。我们开发了一个Android应用程序来实现MotionCompass。我们使用开发的APP和18个流行的无线摄像头进行的广泛实验表明，对于带有一个运动传感器的摄像头，MotionCompass可以在不到140秒的时间内获得约5厘米的平均定位误差。我们还讨论了对MotionCompass的防御。我们的定位技术建立在现有工作的基础上，该工作可以检测隐藏摄像头的存在，以精确定位它们的确切位置。
Wireless cameras nowadays commonly employ motion sensors to identify that something is occurring in their fields of vision before starting to record and notifying the property owner of the activity. In this paper, we discover that the motion sensing action can disclose the location of the camera through a novel wireless camera localization technique we call MotionCompass. By creating motion stimuli and sniffing wireless traffic for a response to that stimuli, a user can obtain the motion trajectories within the motion detection zone and then use them to calculate the camera's location. We also extend the camera localization algorithm to pinpoint cameras in always-active mode. We develop an Android app to implement MotionCompass. Our extensive experiments using the developed app and 18 popular wireless cameras demonstrate that for cameras with one motion sensor, MotionCompass can attain a mean localization error of around 5 cm with less than 140 seconds. We also discuss defenses against MotionCompass. Our localization technique builds upon existing work that detects the existence of hidden cameras, to pinpoint their exact location.