With the assistance of the Internet of Things, the fast developing Healthcare Internet of Things (H-IoT) has promoted the healthcare ecosystem into the era of Health 5.0 and enables many promising medical applications, such as remote healthcare that is crucial in pandemic (e.g., coronavirus disease 2019). Healthcare participants can make accurate diagnosis, treatment, and research based on the shared personal health records (PHRs) sensed from remote H-IoT devices. However, current H-IoT systems fall short of a secure and trustworthy PHR sharing service in remote healthcare, which is able to prevent user privacy leakage and PHR integrity violation together with high efficiency in key distribution alongside efficient data retrieval and fine-grained access control. In response, we present a blockchain-based hierarchical data sharing framework (BHDSF) to provide fine-grained access control and efficient retrieval over encrypted PHRs with low consumed hierarchical key distribution and key leakage resistance. Compared with the existing solutions, the BHDSF takes both untrusted cloud and malicious auditor into consideration simultaneously and achieves trustworthy PHR integrity auditing and metadata verification by leveraging the blockchain technique. Besides, the BHDSF enables efficiently aggregative authentication for the trustworthiness of source records from H-IoT devices, which is lacked in most of the existing data sharing frameworks. Finally, we demonstrate the feasibility of the BHDSF by conducting extensive empirical tests over a real-world dataset.

Fog-assisted Internet of Things (IoT) can outsource the massive data of resource-constraint IoT devices to cloud and fog nodes (FNs). Meanwhile, it enables convenient and low time-delay data-sharing services, which relies heavily on high security of data confidentiality and fine-grained access control. Many efforts have been focused on this urgent requirement by leveraging ciphertext-policy attribute-based encryption (CP-ABE). However, when deployed in fog-assisted IoT systems for secure data sharing, it remains a challenging problem of how to preserve attribute privacy of access policy, and trace-then-revoke traitors (i.e., malicious users intending to leak decryption keys for illegal profits) efficiently and securely in such a large scale and decentralized environment with resource-constraint user devices, especially in consideration of misbehaving cloud and FNs. Therefore, in this article, we propose a revocable and privacy-preserving decentralized data-sharing framework (RPDDSF) by designing a large universe and multiauthority CP-ABE scheme with fully hidden access policy for secure data sharing in IoT systems to achieve user attribute privacy preserving with unbounded attribute universe and key escrow resistance suitable for large scale and decentralized environment. Based on this, with RPDDSF, anyone can efficiently expose the traitors and punish them by forward/backward secure revocation. Besides, RPDDSF is able to guarantee data integrity for both data owners (DOs) and users to resist misbehaving cloud and FNs, alongwith low computation overhead for resource-constraint devices. Finally, RPDDSF is proven to be secure with detailed security proofs, and its high efficiency and feasibility are demonstrated by extensive performance evaluations.

Smart logistics (s-Logistics) has become more and more popular driven by the intelligent Internet of Things (IoT) which deploys pervasive smart devices in s-Logistics systems. The explosive growth of s-Logistics data collected by these resource-limited IoT devices enables Fog-based s-Logistics that provides data outsourcing and sharing services via multiple clouds within small latency. Nevertheless, it also gives rise to prominent security risks of user privacy leakage considering malicious users and data integrity violation with untrusted cloud servers, which are severe to s-Logistics systems and cannot be addressed by simple encryption. To solve these issues, in this article, we propose an efficient large universe and traceable privacy-preserving data sharing (LUTPDS) for Fog-based s-Logistics. It simultaneously achieves data access control, data integrity protection, key escrow and abuse resistance, user privacy preserving, and scalability. We devise a large universe and multiauthority ciphertext-policy attribute-based encryption (CP-ABE) scheme in which access policy hiding mechanism is used for user privacy preserving, while white-box tracing and certificateless public data integrity auditing techniques are employed to resist key abuse and escrow problems. In addition, online/offline encryption and verifiable outsourced decryption are leveraged for high efficiency and cloud encryption is utilized to extend to multiple clouds. In the end, we formally prove the security of our scheme for indistinguishability of chosen plaintext attack (IND-CPA) security and traceability. Detailed performance evaluation with extensive experiments shows that our scheme is practicable for s-Logistics compared with the existing schemes.