论文标题
我总是觉得有人在感知我！检测，识别和本地化秘密无线传感器的框架
I Always Feel Like Somebody's Sensing Me! A Framework to Detect, Identify, and Localize Clandestine Wireless Sensors
论文作者
论文摘要
低成本无线传感器的无处不在，使用户可以轻松地部署系统来远程监视和控制其环境。但是，这引起了第三方乘员的隐私问题，例如可能不知道部署的秘密传感器的旅馆客人。以前的方法着眼于特定模式，例如检测摄像机，但没有提供广泛且全面的方法来捕获可能在用户上“监视”的任意传感器。在这项工作中，我们提出了SnoopDog，这是一个框架，不仅可以检测基于Wi-Fi的常见无线传感器，这些传感器正在积极监视用户，还可以对每个设备进行分类和本地化。 SnoopDog通过在可观察的无线流量中的模式与同一空间中受信任的传感器（例如，惯性测量单元（IMU））建立因果关系来起作用。一旦建立因果关系，Snoopdog就会执行数据包检查，以告知用户监视设备。最后，SnoopDog使用基于新型的基于试验的本地化技术将秘密设备定位在2D平面中。我们评估了跨多种设备和各种方式的窥探者，并能够检测到95.2％的侦探设备的因果关系，并将设备定位为足够降低的子空间。
The increasing ubiquity of low-cost wireless sensors has enabled users to easily deploy systems to remotely monitor and control their environments. However, this raises privacy concerns for third-party occupants, such as a hotel room guest who may be unaware of deployed clandestine sensors. Previous methods focused on specific modalities such as detecting cameras but do not provide a generalized and comprehensive method to capture arbitrary sensors which may be "spying" on a user. In this work, we propose SnoopDog, a framework to not only detect common Wi-Fi-based wireless sensors that are actively monitoring a user, but also classify and localize each device. SnoopDog works by establishing causality between patterns in observable wireless traffic and a trusted sensor in the same space, e.g., an inertial measurement unit (IMU) that captures a user's movement. Once causality is established, SnoopDog performs packet inspection to inform the user about the monitoring device. Finally, SnoopDog localizes the clandestine device in a 2D plane using a novel trial-based localization technique. We evaluated SnoopDog across several devices and various modalities and were able to detect causality for snooping devices 95.2% of the time and localize devices to a sufficiently reduced sub-space.
