Wearable wireless sensor devices are key components in the emerging technology of personalized healthcare monitoring. Medical data collected by these devices must be secured, especially on the wireless link to the gateway equipment. However, it is difficult to manage the required cryptographic keys, as users may lack the awareness or requisite skills for this task. Alternatively, recent work has shown that two communicating devices can generate secret keys derived directly from symmetrical properties of the wireless channel between them. This channel is also strongly dependent on positioning and movement and cannot be inferred in detail by an eavesdropper. Existing schemes, however, yield keys with mismatching bits at the two ends, requiring reconciliation mechanisms with high implementation and energy costs that are unsuitable for resource-poor body-worn devices. In this work we propose a secret-key generation mechanism which uses signal strength fluctuations caused by incidental motion of body-worn devices to construct shared keys with near-perfect agreement, thereby avoiding reconciliation costs. Our contributions are: (1) we analyse channel measurement asymmetries caused by non-simultaneous probing of the channel by the link end-points, (2) we propose a practical filtering scheme to minimize these asymmetries, dramatically improving signal correlation between the two ends without reducing entropy, and (3) we develop a method to restrict key generation to periods of channel fluctuation, ensuring near-perfect key agreement. To the best of our knowledge, this work is the first to demonstrate the feasibility of generating high quality secret keys with zero reconciliation cost in body-worn networks for healthcare monitoring.
The authors in REF investigated the channel 1 https://buy.garmin.com/en-GB/GB/p/136403 property by utilizing the signal strength fluctuation caused by incidental motion of the devices to achieve efficient key construction.
Zero reconciliation secret key generation for body-worn health monitoring devices
WISEC '12
Computer Science