As the complexity of technology and information systems constantly increases, the human component becomes ever more prone to cybersecurity errors. Nevertheless, the existing information security policies created to prevent cybersecurity incidents show very little account of human behavior. This corresponds with the view of the neoclassical economics model that regards humans as rational agents who have perfect self-control and who make only rational choices when provided with adequate information. Behavioral economics introduced quantifiable irrationalities in the model, allowing for an explanation of why humans are often taking decisions that are not in their best interest. This dissertation comprises three studies that explore the influence of cognitive biases and heuristics in cybersecurity. Findings from Study 1 confirm that when presented with a large assortment of choices individuals are more likely to defer their decision than when presented with a small assortment of choices. Also, time constraints are acting as a moderator in the relationship between the number of choices and decision deferral caused by choice overload. Study 2 revealed that the level of fear of missing out is positively correlated with the level of social engineering vulnerability and a negative correlation of information security awareness with social engineering vulnerability was confirmed. Also, an analysis of the influence of information security awareness on the relationship between the level of fear of missing out and the level of social engineering vulnerability indicated a moderation effect. Study 3 emphasized the importance of integrating the habit concept into research on information systems security by revealing a positive correlation between the level of habits in daily life and the level of ISS compliance habits. Also, the study confirmed that ISS training participation is positively correlated with the level of ISS compliance habits strength.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-2353 |
| Date | 01 January 2022 |
| Creators | Alecse, Cristian |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations, 2020- |
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