Harnessing the Ambient Radio Frequency Noise for Wearable Device Pairing

Wearable devices that capture user's rich information regarding their health conditions and daily activities have unmet pairing needs. Today's solutions, which primarily rely on human involvement, are cumbersome, error-prone, and do not scale well. Despite some prior efforts trying to fill this gap, they either rely on some sophisticated sensors, such as electromyogram (EMG) or electrocardiogram (ECG) pads that may not universally exist, or non-trivial design of communication transceivers that cannot be found easily on current commercial devices. Therefore, a pairing scheme for wearable devices that is secure, practical, and convenient is in dire need. In this paper, we propose a novel approach that leverages ambient radio frequency (RF) noise. Our design is based on a key observation that received RF noise power measured in the logarithmic scale at different parts of a human body surface experience the same variation trend, whereas those from different human bodies or off the body are distinct. Wearables make use of the observed noise as the entropy source for the proposed pairing protocol. Extensive experiments show that our scheme has an equal error rate (EER) as low as 1.4% for pairing. Its key generation rate reaches 138 bits/sec, which beats so-far existing pairing schemes. Besides, our scheme can be efficiently executed within 0.97 s. Its incurred energy consumption is as low as 0.27 J for the entire pairing procedure.