People-Centric Urban Sensing: Security Challenges for the New Paradigm

Peter Johnson, Dartmouth College
Apu Kapadia, Dartmouth College
David Kotz, Dartmouth College
Nikos Triandopoulos, Dartmouth College

Report by Dartmouth Department of Computer Science


We study the security challenges that arise in \em people-centric urban sensing, a new sensor-networking paradigm that leverages humans as part of the sensing infrastructure. Most prior work on sensor networks has focused on collecting and processing ephemeral data about the environment using a static topology and an application-aware infrastructure. People-centric urban sensing, however, involves collecting, storing, processing and fusing large volumes of data related to every-day human activities. Sensing is performed in a highly dynamic and mobile environment, and supports (among other things) pervasive computing applications that are focused on enhancing the user's experience. In such a setting, where humans are the central focus, there are new challenges for information security; not only because of the complex and dynamic communication patterns, but also because the data originates from sensors that are carried by a person—not a tiny sensor thrown in the forest or mounted on the neck of an animal. In this paper we aim to instigate discussion about this critical issue—because people-centric sensing will never succeed without adequate provisions for security and privacy. To that end, we outline several important challenges and suggest general solutions that hold promise in this new paradigm of sensor networks.