Secure Online/Offline Data Sharing Framework for Cloud-Assisted Industrial Internet of Things

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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. 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.
Funding Information
  • National Natural Science Foundation of China (61702404, 61702105, U1804263)
  • Fundamental Research Funds for the Central Universities (JB191506)
  • Natural Science Foundation of Shaanxi Province (2019JQ-005)
  • China Postdoctoral Science Foundation (2017M613080)
  • China Scholarship Council (201806965010)
  • National Research Foundation Singapore
  • National Cybersecurity R&D (NRF2018NCR-NSOE004-0001)
  • AXA Research Fund

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