Cybersecurity breaches pose a serious threat to society, potentially causing data leaks, financial losses, and disruptions to critical infrastructure. Identity and Access Management (IAM), a pillar of IT security management, aims to minimize potential attack surfaces. Despite its importance, many organizations struggle to implement effective IAM. An important success factor is data quality: While sufficient data quality is a prerequisite for enabling effective access control, low data quality leads to errors, causing security vulnerabilities and operational costs. This dissertation addresses this problem with research on the assessment and improvement of data quality in IAM. The scope of this research is the quality of access control policies and attributes, with focus areas including quality assessment, quality maintenance, and access reviews. The results were made available in seven peer-reviewed publications, which are part of this cumulative dissertation.
Sascha Kern (Thu,) studied this question.