Run-Time Generation, Transformation, and Verification of Access Control Models for Self-Protection

Self-adaptive access control, in which self- * properties are applied to protecting systems, is a promising solution for the handling of malicious user behaviour in complex infras-tructures. A major challenge in self-adaptive access con-trol is ensuring that chosen adaptations are valid, and pro-duce a satisfiable model of access. The contribution of this paper is the generation, transformation and verification of Role Based Access Control (RBAC) models at run-time, as a means for providing assurances that the adaptations to be deployed are valid. The goal is to protect the system against insider threats by adapting at run-time the access control policies associated with system resources, and access rights assigned to users. Depending on the type of attack, and based on the models from the target system and its environment, the adapted access control models need to be evaluated against the RBAC metamodel, and the adapta-tion constraints related to the application. The feasibility of the proposed approach has been demonstrated in the con-text of a fully working prototype using malicious scenarios inspired by a well documented case of insider attack