Securing Data Provenance in Body Area Networks using Lightweight Wireless Link Fingerprints

Wireless bodyworn sensing devices are becoming popular for fitness, sports training and personalized healthcare ap-plications. Securing the 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 data provenance for these devices by exploiting symmetric spatio-temporal characteristics of the wireless link between two communicat-ing parties. Our solution enables both parties to generate closely matching ‘link ’ fingerprints which uniquely associate a data session with a wireless link such that a third party, at a later date, can verify the links the data was communicated on. These fingerprints are very hard for an eavesdropper to forge, lightweight compared to traditional provenance mech-anisms, and allow for interesting security properties such as accountability and non-repudiation. We validate our solu-tion with experiments using bodyworn devices in scenarios approximating actual device deployment, and we present optimization mechanisms. We believe this is a promising first step towards using wireless-link characteristics for data provenance in body area networks