Contact tracing is among the most important interventions to mitigate the spread of any pandemic, usually in the form of manual contact tracing. Smartphone-facilitated digital contact tracing may help to increase tracing capabilities and extend the coverage to those contacts one does not know in person. Most implemented protocols use local Bluetooth Low Energy (BLE) communication to detect contagion-relevant proximity, together with cryptographic protections, as necessary to improve the privacy of the users of such a system. However, current decentralized protocols, including DP3T [T + 20], do not sufficiently protect infected users from having their status revealed to their contacts, which raises fear of stigmatization. We alleviate this by proposing a new and practical solution with stronger privacy guarantees against active adversaries. It is based on the uploadwhat-you-observed paradigm, includes a separation of duties on the server side, and a mechanism to ensure that users cannot deduce which encounter caused a warning with high time resolution. Finally, we present a simulation-based security notion of digital contact tracing in the realideal setting, and prove the security of our protocol in this framework.
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