Sijie Zhuo (University of Auckland), Robert Biddle (University of Auckland and Carleton University, Ottawa), Lucas Betts, Nalin Asanka Gamagedara Arachchilage, Yun Sing Koh, Danielle Lottridge, Giovanni Russello (University of Auckland)

Phishing is when social engineering is used to deceive a person into sharing sensitive information or downloading malware. Research on phishing susceptibility has focused on personality traits, demographics, and design factors related to the presentation of phishing. There is very little research on how a person’s state of mind might impact outcomes of phishing attacks. We conducted a scenario-based in-lab experiment with 26 participants to examine whether workload affects risky cybersecurity behaviours. Participants were tasked to manage 45 emails for 30 minutes, which included 4 phishing emails. We found that, under high workload, participants had higher physiological arousal and longer fixations, and spent half as much time reading email compared to low workload. There was no main effect for workload on phishing clicking, however a post-hoc analysis revealed that participants were more likely to click on task-relevant phishing emails compared to non-relevant phishing emails during high workload whereas there was no difference during low workload. We discuss the implications of state of mind and attention related to risky cybersecurity behaviour.

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MadRadar: A Black-Box Physical Layer Attack Framework on mmWave...

David Hunt (Duke University), Kristen Angell (Duke University), Zhenzhou Qi (Duke University), Tingjun Chen (Duke University), Miroslav Pajic (Duke University)

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SENSE: Enhancing Microarchitectural Awareness for TEEs via Subscription-Based Notification

Fan Sang (Georgia Institute of Technology), Jaehyuk Lee (Georgia Institute of Technology), Xiaokuan Zhang (George Mason University), Meng Xu (University of Waterloo), Scott Constable (Intel), Yuan Xiao (Intel), Michael Steiner (Intel), Mona Vij (Intel), Taesoo Kim (Georgia Institute of Technology)

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Facilitating Threat Modeling by Leveraging Large Language Models

Isra Elsharef, Zhen Zeng (University of Wisconsin-Milwaukee), Zhongshu Gu (IBM Research)

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