Human Behavior Prediction for Risk Analysis

The Conflicting Incentives Risk Analysis (CIRA) method makes predictions about human decisions to characterize risks within the domain of information security. Since traditional behavior prediction approaches utilizing personal features achieve low accuracies in general, there is a need for improving predictive capabilities. Therefore, primary objective this study propose and test psychological approach prediction, which utilizes situations improved accuracy. An online questionnaire was used collecting behavioral trait data enable comparison approaches. Results show that proposed outperforms across range decisions. Additionally, interrater reliabilities are analyzed estimate extent objectivity situation evaluations, providing an indication potential performance when risk analyst needs rely on unobtrusive assessment action-desirability.