A Self-Adaptive Access Control Framework Based on User Attributes Among Heterogeneous Internet of Things Platforms

Internet of Things (IoT) platforms are being actively designed to provide various services to users. However, most IoT platforms are developed in independent environments, causing difficulties in their interoperability. Even though heterogeneous IoT platforms employ the same attribute-based access control (ABAC) model to protect their resources, the attribute representation methods used by these platforms differ. Consequently, a semantic interoperability problem arises, wherein users of one platform cannot access the resources from other platforms, even though these users possess valid attributes. Therefore, this paper proposes a framework that can interoperate by understanding different attribute representation methods among heterogeneous IoT platforms that employ the same ABAC model. Our framework uses self-adaptive modules monitor-analyze-plan-execute over a shared knowledge (MAPE-K) to solve semantic interoperability problems arising from differences in attribute representations, even with valid attributes, enabling access to resources between heterogeneous IoT platforms.