Relational Framework of Cyberattacks: Empirical Evidence from Multistage Incidents.

The increasing scale and operational complexity of cyberattacks have exposed the limitations of static taxonomies for representing multistage threat scenarios. This study addresses the need for more flexible classification models by proposing a relational taxonomy of cyberattacks grounded in documented incidents. Therefore, the main objective is to propose a relational taxonomy that encodes direct transitions across eight groups in a dependency matrix and a directed graph while preserving traceability to MITRE ATT&CK. The taxonomy was validated by an independent panel of experts who assessed methodological clarity and operational utility. The results reveal consistent transition patterns across groups, delineate reproducible escalation routes, and pinpoint cut-off points linked to specific detection and control activities, providing an operational map of progression and intervention. The conclusions show that the taxonomy clarifies escalation paths, strengthens alignment across security monitoring and incident response functions, threat intelligence workflows and training, and provides an operational structure to manage interdependencies, anticipate escalation and focus monitoring on critical points.