Pinpointing Hidden IoT Devices via Spatial-temporal Traffic Fingerprinting

With the popularization of Internet of Things (IoT) devices in smart home and industry fields, a huge number of IoT devices are connected to the Internet. However, what devices are connected to a network may not be known by the Internet Service Provider (ISP), since many IoT devices are placed within small networks (e.g., home networks) and are hidden behind network address translation (NAT). Without pinpointing IoT devices in a network, it is unlikely for the ISP to appropriately configure security policies and effectively manage the network. In this paper, we design an efficient and scalable system via spatial-temporal traffic fingerprinting. Our system can accurately identify typical IoT devices in a network, with the additional capability of identifying what devices are hidden behind NAT and how many they are. Through extensive evaluation, we demonstrate that the system can generally identify IoT devices with an F-Score above 0.999, and estimate the number of the same type of IoT device behind NAT with an average error below 5%. We also perform small-scale (labor-intensive) experiments to show that our system is promising in detecting user-IoT interactions.