Securing First-Hop Data Provenance for Bodyworn Devices Using Wireless Link Fingerprints

Abstract

Wireless bodyworn sensing devices are fast becoming popular for fitness, sports training, and personalized healthcare applications. Securing data generated by these devices is essential if they are to be integrated into the current health infrastructure and employed in medical applications. In this paper, we propose a mechanism to secure the data provenance for these devices by exploiting spatio-temporal characteristics of the wireless channel that these devices use for communication. Our solution enables two parties to generate closely matching link fingerprints, which uniquely associate a data session with a wireless link such that a third party can later verify the details of the transaction, particularly the wireless link on which the data was transmitted. These fingerprints are very hard for an eavesdropper to forge; they are lightweight compared with traditional provenance mechanisms and enable interesting security properties such as accountability, nonrepudiation, and resist man-in-the-middle attacks. We validate our technique with experiments using bodyworn sensors in scenarios approximating actual device deployment and present some extensions, which reduce energy consumption. We believe this is a promising first step toward using wireless-link characteristics for the data provenance in body area networks.