Predicting Cybersecurity Incidents via Self-Reported Behavioral and Psychological Indicators: A Stratified Logistic Regression Approach

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Stratified analysis predicts cybersecurity incidents using psychological and behavioral indicators, highlighting practical applications.

Models improved prediction of cybersecurity incidents by capturing behavioral and contextual specificity, leading to better insights.
Survey data from 453 professionals revealed predictions for multiple outcomes, with suspicious logins yielding robust results.
The logistic regression approach utilized item-level indicators rather than aggregates, increasing interpretability and transparency.
This framework integrates demographic fairness, ensuring ethical deployment of models within diverse organizational contexts.

László Bognár (2025) studied this question.

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