Privacy-preserving fine-grained data sharing with dynamic service for the cloud-edge IoT - SUN, Jianfei (Institutional Knowledge at Singapore Management University, 2024)
The cloud-edge computing model has been expected to play a revolutionary role in promoting the quality of future generation large-scale Internet of Things (IoT) services. However, security and privacy in data sharing remain crucial issues hindering the success of cloud-edge IoT services. While some solutions based on attribute-based encryption (ABE) have been proposed to address these issues, they still face practical challenges such as attribute privacy leakage, resource-constrained devices, dynamic user groups, inflexible and inefficient service response. To address these challenges, this paper proposes a privacy-preserving fine-grained data sharing scheme with dynamic service (PF2DS), which implements access control by calculating the inner product between an attribute vector and an access vector. PF2DS is also capable of providing dynamic user group services through an efficient and indirect user revocation mechanism that periodically updates the key-embedded leaf nodes. Building on PF2DS, edge-assisted PF2DS (EPF2DS) delegates most of the operations to the edge device, which facilitates the performance of resource-constrained IoT devices. EPF2DS also supports efficient and asynchronous keyword search over the ciphertexts stored in the cloud. We demonstrate the security by the rigorous security proof. Both theoretical comparisons and experimental simulations demonstrate the practicality and superiority of our schemes over existing works.