Abstract
In recent years, wearable smart devices have entered people’s lives. These devices can help users to record their daily activities, health data and so on. These devices periodically send out packets to keep connected with mobile phones, which can be observed by any external observer. By analyzing these packets, some information about the device owner will be revealed. Although the observer can sniff the wireless packets, the actual person using the device is unknown. In this paper, we link wearable smart devices with users’ mobile phones which are recognized as users’ electronic identity. Linking these two types of devices opens up new opportunities for applications such as authenticating users by multi-devices or constructing user device graph for advertisements. We deploy sniffing nodes to sniff BLE and WiFi signals, and put forward a multi-stage filtering method to reduce signals’ noises, then link two types of devices by an algorithm based on dynamic time warping. At last, our experiments show that 7 wearable devices can be linked with a correct rate more than 80%. We also find that when one device is observed more than 11 times, its linking accuracy can be close to 100%.
Published Version
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