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In the context of the emerging Internet of Things (IoT), a proliferation ofwireless connectivity can be expected. That ubiquitous wireless communicationwill be hard to centrally manage and control, and can be expected to be opaqueto end users. As a result, owners and users of physical space are threatened tolose control over their digital environments.  In this work, we propose the idea of an IoTScanner. The IoTScanner integratesa range of radios to allow local reconnaissance of existing wirelessinfrastructure and participating nodes. It enumerates such devices, identifiesconnection patterns, and provides valuable insights for technical support andhome users alike. Using our IoTScanner, we attempt to classify activelystreaming IP cameras from other non-camera devices using simple heuristics. Weshow that our classification approach achieves a high accuracy in an IoTsetting consisting of a large number of IoT devices. While related work usuallyfocuses on detecting either the infrastructure, or eavesdropping on trafficfrom a specific node, we focus on providing a general overview of operations inall observed networks. We do not assume prior knowledge of used SSIDs,preshared passwords, or similar.

IoTScanner: Detecting and Classifying Privacy Threats in IoT Neighborhoods