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Phishing attack countermeasures have previously relied on technical solutions or user training. As phishing attacks continue to impact users resulting in adverse consequences, mitigation efforts may be strengthened through an understanding of how user characteristics predict phishing susceptibility. Several studies have identified factors of interest that may contribute to susceptibility. Others have begun to build predictive models to better understand the relationships among factors in addition to their prediction power, although these studies have only used a handful of predictors. As a step toward creating a holistic model to predict phishing susceptibility, it was first necessary to catalog all known predictors that have been identified in the literature. We identified 32 predictors related to personality traits, demographics, educational background, cybersecurity experience and beliefs, platform experience, email behaviors, and work commitment style.
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This content will become publicly available on May 9, 2026
Development of a User-Focused Hexahedral Meshing Software for Swept Surfaces
Hexahedral meshing plays a critical role in high fidelity computational solid mechanics. However, many tools remain inaccessible due to the cost of purchase or a poor user experience. In this work, we describe efforts to facilitate a highquality user experience with a new hexahedral meshing software developed using topological sweeping operations. These efforts include integrating the tool with existing software for engineering design, preprocessing, meshing, and visualization; creating a Python-based application protocol interface (API) to allow for easier scripting and interactions without requiring experience in C++; creating a user manual to discuss how to operate the software; and performing a simple case study on five potential users of various background about how to interact with the software. Feedback indicated the value of providing additional background and examples and will help improve future work on the user experience of this software in order to ultimately create a meaningful tool for educational and industrial use.
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- Award ID(s):
- 2245491
- PAR ID:
- 10631486
- Publisher / Repository:
- IEEE
- Date Published:
- ISBN:
- 979-8-3315-1282-8
- Page Range / eLocation ID:
- 1 to 5
- Format(s):
- Medium: X
- Location:
- Orem, UT, USA
- Sponsoring Org:
- National Science Foundation
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