Secure Online/Offline Data Sharing for Industrial Internet of Things

Abstract-Ciphertext-policy attribute-based keyword search (CP-ABKS) schemes facilitate the fine-grained keyword search over encrypted data, such as those sensed/collected from Industrial Internet of Things (IIoT) devices and stored in the cloud. However, existing CP-ABKS schemes generally have significant computation and storage requirements, which are beyond those of resource-constrained IIoT devices. Therefore, in this paper, we design a secure online/offline Data Sharing Framework (DSF), which supports online/offline encryption and outsourced decryption. DSF is based on requirements from automation pilots and the General Data Protection Regulation. Updates based on the DSF’s implementation experience over the last few years were added in the latest version (v1. 1) of the framework. Using the healthcare setting as a case study, we demonstrate how DSF can be deployed in the cloud-assisted Healthcare IIoT (HealthIIoT) system. We not only prove that the DSF is selectively secure in the chosen access structure security model, but also demonstrate its efficiency and feasibility in practical scenarios using experiments.