Methodology for hybrid role development

Viac o knihe

“Cybercrime costs firms USD 1 trillion globally” – Headlines like this from Reuters highlight the pressing issue of data security. Surveys reveal that insiders, particularly employees, pose significant threats to data integrity. Improper account management leads to excessive rights accumulation, resulting in identity chaos. As IT infrastructures expand and regulations tighten, role-based Identity Management has emerged as a solution to address this chaos and enhance data security. A key challenge for organizations is constructing a role catalogue for their Identity Management systems. Some rely on manual procedures based on their operational structures, known as Role Engineering methodologies. In contrast, Role Mining methodologies, which leverage Data Mining techniques to cluster existing employee access rights, have gained traction. Recent studies indicate that a combination of Role Engineering and Role Mining is essential for defining effective roles. This work offers insights into a hybrid tool-supported methodology for cleansing identity and account data while developing business roles for employees. Its primary objectives are to enhance user management data quality and facilitate a semi-automated process for role definition, taking into account employee information, access privileges, organizational structures, and the expertise of business professionals.