Summary form only given. First part of this talk will discuss how the community is converging towards the IoT vision having worked in wireless sensor networking and Machine-2-Machine (M2M) communication. This will follow a general discussion of security challenges in IoT. Finally I will discuss some results from an ongoing project on security of bodyworn devices. Wireless bodyworn sensing devices are becoming popular for fitness, sports training and personalized healthcare applications. 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 talk, I will discuss a mechanism to secure data provenance for these devices by exploiting symmetric spatio-temporal characteristics of the wireless link between two communicating 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 mechanisms, and allow for interesting security properties such as accountability and non-repudiation. I will present our solution with experiments using bodyworn devices in scenarios approximating actual device deployment.