The exponential growth of wearable medical devices (WMDs) and the increasing demand for real-time health data sharing necessitate secure and fine-grained access control mechanisms. However, existing ciphertext-policy attribute-based encryption (CP-ABE) schemes suffer from computational and storage overheads that grow linearly with policy complexity. To address this challenge, we propose fog-assisted composite attribute-based encryption (FA-CABE), a novel scheme that integrates composite attributes with fog computing to enhance efficiency. FA-CABE leverages the subset sum problem (SSP) to map conjunctive policy clauses to composite attributes, substantially reducing both encryption and decryption overhead. A dualfog-node architecture offloads cryptographic computations from WMDs, enabling lightweight local processing. Rigorous security analysis under the Decisional Bilinear Diffie-Hellman (DBDH) assumption demonstrates that FA-CABE achieves replayable chosen ciphertext attack (RCCA) security. Experimental results show that FA-CABE achieves encryption speeds that are 22.13×–145.02× faster and decryption speeds that are 6.71×–161.83× faster than existing schemes, while requiring only a constant number of operations for decryption. Additionally, experimental validation on the Raspberry Pi 4B shows that the energy consumption is as low as 0.72 W per core, with data processing speed reaching 23.38 MB/s.

As the Industrial Internet of Things (IIoT) expands, the number of stakeholders increases. Many entities require significant amounts of data from industrial devices. These data streams improve information sharing and optimize the industrial chain. However, IIoT’s enormous data volumes pose challenges to traditional encryption methods, which are unable to meet efficiency and energy consumption requirements. Thus, a new, efficient encryption algorithm is essential for managing data flows among IIoT subscribers. In this paper, we propose a fast, low-energy, high-security encryption scheme to manage multi-entity data streams. First, we introduce a novel encryption scheme based on the Subset Sum Problem (SSP), which improves energy efficiency and speed. Second, to meet subscription requirements, we employ attribute-based encryption (ABE) for key forwarding. Finally, we handle subscription revocations with device key updates. The device owner utilizes their secret value to generate an identity proof with a key update request.

With the advent of various mobile IoT devices, a large amount of e-health record (EHR) data has been generated. This data has great potential to improve medical research. However, there are many challenges regarding the sharing of medical data. Firstly, users are more inclined to interact anonymously. Secondly, verifying the validity of certificates in the case of anonymous interactions is challenging. In addition, it is necessary to uncover the identities of the actual interacting parties in the event of malicious behavior. Therefore, we address the above challenges and propose group signatures with time constraints to support anonymous and traceable EHR data sharing. First, we propose a group signature scheme that supports traceability. Second, to address the issue of validating anonymous certificates, we propose group signatures with time constraints that enable dynamic updates to validity. Through this, we can dynamically revoke group members. Lastly, security proofs and efficiency analyses demonstrate that our scheme is both secure and efficient.