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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Data Poisoning Attacks to Deep Learning Based Recommender Systems

Hai Huang (Tsinghua University), Jiaming Mu (Tsinghua University), Neil Zhenqiang Gong (Duke University), Qi Li (Tsinghua University), Bin Liu (West Virginia University), Mingwei Xu (Tsinghua University)

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Empirical Scanning Analysis of Censys and Shodan

Christopher Bennett, AbdelRahman Abdou, and Paul C. van Oorschot (School of Computer Science, Carleton University, Canada)

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FARE: Enabling Fine-grained Attack Categorization under Low-quality Labeled Data

Junjie Liang (The Pennsylvania State University), Wenbo Guo (The Pennsylvania State University), Tongbo Luo (Robinhood), Vasant Honavar (The Pennsylvania State University), Gang Wang (University of Illinois at Urbana-Champaign), Xinyu Xing (The Pennsylvania State University)

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Demo #5: Securing Heavy Vehicle Diagnostics

Jeremy Daily, David Nnaji, and Ben Ettlinger (Colorado State University)

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