AI/ML, Graphs and Access Control: Towards Holistic Identity and Access Management

Vulnerabilities in identity and access management (IAM) are one of the most common reasons for data breaches leading to adversarial impacts on security, privacy and compliance postures. Account breaches, incorrectly designed access control policies, weaknesses in authentication and credential management, vulnerable session management are some of the several security issues that lead to eventual compromise of the crown jewels leading to data breaches. The lifecycles of subjects and their identities, of objects and re- sources, and of the permissions and authorization policies are in- tertwined in a complex manner for each specific scenario. Often subjects, objects and permissions often are hard to be defined or isolated from each other, especially in the context of machine learn-ing. The evolution of these entities, and how their provenance is analyzed often is essential not only for forensic analysis of a breach but also should be a proactive ongoing process.