Jens Christian Dalgaard, Niek A. Janssen, Oksana Kulyuk, Carsten Schurmann (IT University of Copenhagen)

Cybersecurity concerns are increasingly growing across different sectors globally, yet security education remains a challenge. As such, many of the current proposals suffer from drawbacks, such as failing to engage users or to provide them with actionable guidelines on how to protect their security assets in practice. In this work, we propose an approach for designing security trainings from an adversarial perspective, where the audience learns about the specific methodology of the specific methods, which attackers can use to break into IT systems. We design a platform based on our proposed approach and evaluate it in an empirical study (N = 34), showing promising results in terms of motivating users to follow security policies.

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PPA: Preference Profiling Attack Against Federated Learning

Chunyi Zhou (Nanjing University of Science and Technology), Yansong Gao (Nanjing University of Science and Technology), Anmin Fu (Nanjing University of Science and Technology), Kai Chen (Chinese Academy of Science), Zhiyang Dai (Nanjing University of Science and Technology), Zhi Zhang (CSIRO's Data61), Minhui Xue (CSIRO's Data61), Yuqing Zhang (University of Chinese Academy of Science)

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Blaze: A Framework for Interprocedural Binary Analysis

Matthew Revelle, Matt Parker, Kevin Orr (Kudu Dynamics)

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Location Data and COVID-19 Contact Tracing: How Data Privacy...

Callie Monroe, Faiza Tazi, Sanchari Das (university of Denver)

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FUZZILLI: Fuzzing for JavaScript JIT Compiler Vulnerabilities

Samuel Groß (Google), Simon Koch (TU Braunschweig), Lukas Bernhard (Ruhr-University Bochum), Thorsten Holz (CISPA Helmholtz Center for Information Security), Martin Johns (TU Braunschweig)

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