Simon Parkin (TU Delft), Kristen Kuhn, Siraj Ahmed Shaikh (Coventry University)

The motivation for corporate leadership to engage with cyber risks is increasingly clear. Stories can be seen of cyber incidents which have crippled large-scale businesses, potentially for extended periods of time and at significant cost. Our contribution here explores a much under-researched area — perceptions of cybersecurity and cyber risk at the highest levels of an organisation — with the aim of developing a structured, scenario-driven and repeatable exercise for executive decision makers. We attempt to understand why cyber risk perception is an important concept but equally a challenging one to grasp. We address this by demonstrating an approach to risk articulation, in terms of systematically constructed scenarios, and assess whether this resonates with decision-makers. As part of this, we also attempt to assess cyber-risk decision-makers for their perception of wider business risks and stakeholders.

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Designing a Mobile App to Support Social Processes for...

Zaina Aljallad (University of Central Florida); Wentao Guo (Pomona College); Chhaya Chouhan, Christy Laperriere (University of Central Florida); Jess Kropczynski (University of Cincinnati); Pamela Wisnewski (University of Central Florida); Heather Lipford (University of North Carolina at Charlotte)

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Stop to Unlock: Improving the Security of Android Unlock...

Alexander Suchan (SBA Research); Emanuel von Zezschwitz (Usable Security Methods Group, University of Bonn, Bonn, Germany); Katharina Krombholz (CISPA Helmholtz Center for Information Security)

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Augmented Reality’s Potential for Identifying and Mitigating Home Privacy...

Stefany Cruz (Northwestern University), Logan Danek (Northwestern University), Shinan Liu (University of Chicago), Christopher Kraemer (Georgia Institute of Technology), Zixin Wang (Zhejiang University), Nick Feamster (University of Chicago), Danny Yuxing Huang (New York University), Yaxing Yao (University of Maryland), Josiah Hester (Georgia Institute of Technology)

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Demo #10: Security of Deep Learning based Automated Lane...

Takami Sato, Junjie Shen, Ningfei Wang (UC Irvine), Yunhan Jia (ByteDance), Xue Lin (Northeastern University), and Qi Alfred Chen (UC Irvine)

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