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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Demo #2: Sequential Attacks on Kalman Filter-Based Forward Collision...

Yuzhe Ma, Jon Sharp, Ruizhe Wang, Earlence Fernandes, and Jerry Zhu (University of Wisconsin–Madison)

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icLibFuzzer: Isolated-context libFuzzer for Improving Fuzzer Comparability

Yu-Chuan Liang, Hsu-Chun Hsiao (National Taiwan University)

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Data Analytics and Expert Judgment in Time of Crisis:...

Igor Linkov, PhD Senior Science and Technology Manager, US Army Engineer Research and Development Center; Senior Data Analyst (on detail), FEMA/HHS R1 COVID Task Force; Adjunct Professor, Carnegie Mellon University

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Cross-National Study on Phishing Resilience

Shakthidhar Reddy Gopavaram (Indiana University), Jayati Dev (Indiana University), Marthie Grobler (CSIRO’s Data61), DongInn Kim (Indiana University), Sanchari Das (University of Denver), L. Jean Camp (Indiana University)

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