UC Berkeley

We explore the challenges of implementing a privacy-preserving opportunistic data collection network for resource-constrained edge IoT devices. Opportunistic networks require no fixed infrastructure and allow edge devices to piggy-back messages through stationary or mobile gateways. Research interest in such networks has waxed and waned over the years, but commercial deployments have not taken off until recently. Over the past year, we have witnessed a resurgence of interest fueled by wide-scale commercial deployments, most notably Amazon's Sidewalk network, but also Apple's Find My and the Tile network. As these networks become more prevalent, maintaining the privacy of the individuals who participate in them will become increasingly important. In this paper, we demonstrate that current opportunistic networks leak access patterns to the network operator itself through communication metadata, which can be used to reconstruct location traces. We argue that opportunistic networks and privacy are not mutually exclusive, and suggest some potential research directions to strengthen the privacy properties of these networks. Since opportunistic networks are now being deployed at massive scale, we argue that the time is ripe to make them privacy-preserving before it is too late.