Understanding the operators’ cloud change errors based on cognitive abilities and personality traits: An investigation integrated with quantitative and qualitative methods

Abstract

While cloud services make industrial data convenient, they also expose it to cloud incidents. Operators' error in cloud change activities is a leading factor for cloud incidents, which have received relatively less attention in cloud security research. This study conducted a two-stage research process using an integrated approach to explore the stable individual factors related to cloud change errors. First, in the qualitative research, content analysis based on interviews and historical documents was conducted to extract the operator's cognitive abilities and personality traits and develop hypotheses. Five cognitive abilities and six personality traits were extracted. Second, quantitative research based on an experiment was conducted to test relationships between operators' different types of cloud change errors and 1) cognitive ability and 2) personality traits, respectively. Results of error type comparisons suggested that operators generated more uncorrected errors than corrected errors and more operational errors than omission errors in cloud change activities. The multivariate Poisson regression analysis suggested that cognitive abilities of sustained attention, divided attention, and long-term memory negatively predicted the number of operators' total errors, uncorrected errors, and operational errors. Regarding personality traits, with the increase in resilience capacity and carefulness and the decrease in self-esteem, the number of different types of errors reduced, except for omission errors. Working memory and risk-taking propensity were also significant predictors of the number of uncorrected errors with negative and positive coefficients, respectively. Logical reasoning, emotional stability, and sense of responsibility were not observed as predictors of cloud change errors. The present findings have several implications for the industry and cloud providers to enhance industrial cloud data security regarding human cognitive abilities and personality traits.