DRiBAC: Fine-grained dynamic role interaction access control using ontology

Multiagent systems are characterized by enriched interactions among agents, which have dynamic and autonomous behavior, towards achieving some common goals. Such interactions involve accessing an agent´s resources and functionalities by other agents. It is critical that such interactions are secure and agents engage in only authorized interactions based on their roles. In this paper, we propose a fine-grained Dynamic Role Interaction Access Control (DRiBAC) model to support exclusive authorization for agents that need to engage in interactions with other agents by dynamic assignments of roles and permissions and their activations. We extend an earlier proposed RiBAC model with the notion of role interaction and interaction assignment and context-aware constraints. To capture the model and its context, and to support semantic reasoning of DRiBAC policies, we propose DRiBAC ontology and illustrate its use on an example online tutoring system.