Variable Self-Efficacy as a Measurement for Behaviors in Cyber Security Operations

Training and development of skills gives individuals the knowledge and procedures required to perform their tasks. Training also requires individuals to develop reflective skills that help consolidate and transfer knowledge to long-term memory, where it then can be recalled in appropriate situations. But to develop reflective skills, one must first engage with the task’s demands and then analyse how one’s skills were appropriate or not for the situational demands, and how one could have also approached the situation differently. This process leads to an adaptable self-efficacy. It is still unclear how personality trait measures of self-efficacy can predict performance in cyber security operations. We developed an adaptable self-efficacy measure which was collected via an app. Findings support previous research that specific self-efficacy has better predictive validity, but also finds that an increased number of measurements could yield better effect sizes. This research shows how multiple measurements of specific self-efficacy can be done with minimized invasiveness while providing better measurement reliability and predictability. General findings and implications for further research are also discussed.