Leonie Reichert and Samuel Brack (Humboldt University of Berlin); Björn Scheuermann (Humboldt-University of Berlin)

The COVID-19 pandemic created various new challenges for our societies. Quickly discovering new infections using automated contact tracing without endangering privacy of the general public is one of these. Most discussions concerning architectures for contact tracing applications revolved around centralized against decentralized approaches. In contrast, the system proposed in this work builds on the idea of message based contact tracing to inform users about their risk. Our main contribution is the combination of a blind-signature approach to verify infections with an anonymous postbox service. In our evaluation, we analyze all components in our system for performance and privacy, as well as security. We also derive parameters for operating our system in a pandemic scenario.

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To Err.Is Human: Characterizing the Threat of Unintended URLs...

Beliz Kaleli (Boston University), Brian Kondracki (Stony Brook University), Manuel Egele (Boston University), Nick Nikiforakis (Stony Brook University), Gianluca Stringhini (Boston University)

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OblivSketch: Oblivious Network Measurement as a Cloud Service

Shangqi Lai (Monash University), Xingliang Yuan (Monash University), Joseph K. Liu (Monash University), Xun Yi (RMIT University), Qi Li (Tsinghua University), Dongxi Liu (Data61, CSIRO), Surya Nepal (Data61, CSIRO)

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LaKSA: A Probabilistic Proof-of-Stake Protocol

Daniel Reijsbergen (Singapore University of Technology and Design), Pawel Szalachowski (Singapore University of Technology and Design), Junming Ke (University of Tartu), Zengpeng Li (Singapore University of Technology and Design), Jianying Zhou (Singapore University of Technology and Design)

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Debunking Exposure Notification

Serge Vaudenay, EPFL, Switzerland

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