Onion Routing with Replies 📺
Onion routing (OR) protocols are a crucial tool for providing anonymous internet communication. An OR protocol enables a user to anonymously send requests to a server. A fundamental problem of OR protocols is how to deal with replies: ideally, we would want the server to be able to send a reply back to the anonymous user without knowing or disclosing the user's identity. Existing OR protocols do allow for such replies, but do not provably protect the payload (i.e., message) of replies against manipulation. Kuhn et al. (IEEE S&P 2020) show that such manipulations can in fact be leveraged to break anonymity of the whole protocol. In this work, we close this gap and provide the first framework and protocols for OR with protected replies. We define security in the sense of an ideal functionality in the universal composability model, and provide corresponding (less complex) game-based security notions for the individual properties. We also provide two secure instantiations of our framework: one based on updatable encryption, and one based on succinct non-interactive arguments (SNARGs) to authenticate payloads both in requests and replies. In both cases, our central technical handle is an implicit authentication of the transmitted payload data, as opposed to an explicit, but insufficient authentication (with MACs) in previous solutions. Our results exhibit a new and surprising application of updatable encryption outside of long-term data storage.
ConTra Corona: Contact Tracing against the Coronavirus by Bridging the Centralized–Decentralized Divide for Stronger Privacy 📺
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, 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 upload-what-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 real–ideal setting, and prove the security of our protocol in this framework.