IoTrace: A Flexible, Efficient, and Privacy-Preserving IoT-enabled Architecture for Contact Tracing

TL;DR

IoTrace introduces a flexible, privacy-preserving IoT-based contact tracing architecture that minimizes user overhead and supports various social interaction models, enhancing privacy and adaptability over traditional smartphone-centric solutions.

Contribution

The paper presents an IoT-enabled contact tracing architecture that reduces user overhead, enhances privacy with k-anonymity, and supports multiple social interaction models, unlike existing smartphone-centric solutions.

Findings

Reduces user overhead to only broadcasting beacons.

Provides k-anonymity for enhanced privacy.

Supports multiple contact tracing models through configurable system parameters.

Abstract

Contact tracing promises to help fight the spread of Covid-19 via an early detection of possible contagion events. To this end, most existing solutions share the following architecture: smartphones continuously broadcast random beacons that are intercepted by nearby devices and stored into their local contact logs. In this paper, we propose an IoT-enabled architecture for contact tracing that relaxes the smartphone-centric assumption, and provide a solution that enjoys the following features: (i) it reduces the overhead on the end-user to the bare minimum -- the mobile device only broadcasts its beacons; (ii) it provides the user with a degree of privacy not achieved by competing solutions -- even in the most privacy adverse scenario, the solution provides k-anonymity; and, (iii) it is flexible: the same architecture can be configured to support several models -- ranging from the fully decentralized to the fully centralized ones -- and the system parameters can be tuned to support the tracing of several social interaction models. We also highlight open issues and discuss a number of future research directions.