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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Eavesdropping on Black-box Mobile Devices via Audio Amplifier's EMR

Huiling Chen (College of Computer Science and Electronic Engineering, Hunan University, Changsha, China), Wenqiang Jin (College of Computer Science and Electronic Engineering, Hunan University, Changsha, China), Yupeng Hu (College of Computer Science and Electronic Engineering, Hunan University, Changsha, China), Zhenyu Ning (College of Computer Science and Electronic Engineering, Hunan University, Changsha, China), Kenli Li (College…

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A Security and Usability Analysis of Local Attacks Against...

Tarun Kumar Yadav (Brigham Young University), Kent Seamons (Brigham Young University)

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Compensating Removed Frequency Components: Thwarting Voice Spectrum Reduction Attacks

Shu Wang (George Mason University), Kun Sun (George Mason University), Qi Li (Tsinghua University)

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WIP: Threat Modeling Laser-Induced Acoustic Interference in Computer Vision-Assisted...

Nina Shamsi (Northeastern University), Kaeshav Chandrasekar, Yan Long, Christopher Limbach (University of Michigan), Keith Rebello (Boeing), Kevin Fu (Northeastern University)

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