The Impact of Phishing Susceptibility on Different Individual Outcomes
Bibliographic record
Abstract
Phishing attacks have become a serious cybersecurity issue by exploiting people's vulnerabilities through deceitful tactics. While the effects on organizations are well established, the individual-level implications require further investigation. The purpose of this study is to comprehensively evaluate the literature on the individual outcome of phishing susceptibility, which is divided into four domains: behavioral, work performance, psychological, and financial. The Technology Threat Avoidance Theory (TTAT) offered a framework for the study to examine how individuals perceive and respond to phishing threats, focusing on threat appraisal, coping mechanisms, and the cost-benefit dynamics of protective actions. Key findings reveal that phishing susceptibility can lead to outcomes such as altered cybersecurity behaviors. The study shows how phishing affects individuals beyond immediate security breaches and contributes to the growing knowledge of phishing susceptibility prevention and its impacts on academia and cybersecurity. The review calls for tailored interventions to mitigate the multifaceted impacts of phishing
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".