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.

View More Papers

Ghost Domain Reloaded: Vulnerable Links in Domain Name Delegation...

Xiang Li (Tsinghua University), Baojun Liu (Tsinghua University), Xuesong Bai (University of California, Irvine), Mingming Zhang (Tsinghua University), Qifan Zhang (University of California, Irvine), Zhou Li (University of California, Irvine), Haixin Duan (Tsinghua University; QI-ANXIN Technology Research Institute; Zhongguancun Laboratory), Qi Li (Tsinghua University; Zhongguancun Laboratory)

Read More

Analyzing and Creating Malicious URLs: A Comparative Study on...

Vincent Drury (IT-Security Research Group, RWTH Aachen University), Rene Roepke (Learning Technologies Research Group, RWTH Aachen University), Ulrik Schroeder (Learning Technologies Research Group, RWTH Aachen University), Ulrike Meyer (IT-Security Research Group, RWTH Aachen University)

Read More

A Study on Security and Privacy Practices in Danish...

Asmita Dalela (IT University of Copenhagen), Saverio Giallorenzo (Department of Computer Science and Engineering - University of Bologna), Oksana Kulyk (ITU Copenhagen), Jacopo Mauro (University of Southern Denmark), Elda Paja (IT University of Copenhagen)

Read More

Short: Certifiably Robust Perception Against Adversarial Patch Attacks: A...

Chong Xiang (Princeton University), Chawin Sitawarin (University of California, Berkeley), Tong Wu (Princeton University), Prateek Mittal (Princeton University)

Read More