Investigating Cloud Computing Misconfiguration Errors using the Human Factors Analysis and Classification System

Abstract

Abstract As organizations raced to leverage cloud computing to capitalize on its economic and flexible computing capacity, misconfiguration errors ascended to unprecedented levels. One security expert noted observing over 230 million misconfigurations daily. Cloud misconfiguration errors are problematic as malicious actors continually pursue missteps to gain unauthorized access. The complexity of cloud computing coupled with increased cloud usage and the lack of cloud expertise result in misconfiguration errors which are human errors. Leveraging the human factors analysis and classification system (HFACS) provides a framework for identifying and preventing causal pathways for misconfiguration errors. In cloud computing, practitioners can explore the linkages of the hierarchical levels and decision-making at each level that influences and enable the misconfigurations. Human errors in cybersecurity are rampant, and HFACS could provide comprehensive analyses to highlight how errors, mistakes, and violations propagate misconfiguration errors – a current blind spot in cloud computing.