Asangi Jayatilaka (Centre for Research on Engineering Software Technologies (CREST), The University of Adelaide, School of Computing Technologies, RMIT University), Nalin Asanka Gamagedara Arachchilage (School of Computer Science, The University of Auckland), M. Ali Babar (Centre for Research on Engineering Software Technologies (CREST), The University of Adelaide)

Despite technical and non-technical countermeasures, humans continue to be tricked by phishing emails. How users make email response decisions is a missing piece in the puzzle to identifying why people still fall for phishing emails. We conducted an empirical study using a think-aloud method to investigate how people make ‘response decisions’ while reading emails. The grounded theory analysis of the in-depth qualitative data has enabled us to identify different elements of email users’ decision-making that influence their email response decisions. Furthermore, we developed a theoretical model that explains how people could be driven to respond to emails based on the identified elements of users’ email decision-making processes and the relationships uncovered from the data. The findings provide deeper insights into phishing email susceptibility due to people’s email response decision-making behavior. We also discuss the implications of our findings for designers and researchers working in anti-phishing training, education, and awareness interventions.

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AnonPSI: An Anonymity Assessment Framework for PSI

Bo Jiang (TikTok Inc.), Jian Du (TikTok Inc.), Qiang Yan (TikTok Inc.)

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MASTERKEY: Automated Jailbreaking of Large Language Model Chatbots

Gelei Deng (Nanyang Technological University), Yi Liu (Nanyang Technological University), Yuekang Li (University of New South Wales), Kailong Wang (Huazhong University of Science and Technology), Ying Zhang (Virginia Tech), Zefeng Li (Nanyang Technological University), Haoyu Wang (Huazhong University of Science and Technology), Tianwei Zhang (Nanyang Technological University), Yang Liu (Nanyang Technological University)

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Separation is Good: A Faster Order-Fairness Byzantine Consensus

Ke Mu (Southern University of Science and Technology, China), Bo Yin (Changsha University of Science and Technology, China), Alia Asheralieva (Loughborough University, UK), Xuetao Wei (Southern University of Science and Technology, China & Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation, SUSTech, China)

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