Personal health records (PHRs) are private and vital assets for every patient. There have been introduced many works on various aspects of managing and organizing the PHR so far. However, there is an uncertain remaining issue for the role of PHR in emergencies. In a traditional emergency access system, the patient cannot give consent to emergency staff for accessing his/her PHR. Moreover, there is no secured record management of patient's PHR, which reveals highly confidential personal information, such as what happened, when, and who has access to such information. This paper proposes an emergency access control management system (EACMS) based on permissioned blockchain hyperledger fabric and hyperledger composer. In the proposed system, we defined some rules using the smart contracts for emergency condition and time duration for the emergency access PHR data items that patient can assign some limitations for controlling the PHR permissions. We analyzed the performance of our proposed framework by implementing it through the hyperledger composer based on the response time, privacy, security, and accessibility. The experiments confirm that our framework provides better efficiency compared with the traditional emergency access system.

Nowadays, wireless body area networks (WBANs) systems have adopted cloud computing (CC) technology to overcome limitations such as power, storage, scalability, management, and computing. This amalgamation of WBANs systems and CC technology, as sensor‐cloud infrastructure (S‐CI), is aiding the healthcare domain through real‐time monitoring of patients and the early diagnosis of diseases. Hence, the distributed environment of S‐CI presents new threats to patient data privacy and security. In this paper, we review the techniques for patient data privacy and security in S‐CI. Existing techniques are classified as multibiometric key generation, pairwise key establishment, hash function, attribute‐based encryption, chaotic maps, hybrid encryption, Number Theory Research Unit, Tri‐Mode Algorithm, Dynamic Probability Packet Marking, and Priority‐Based Data Forwarding techniques, according to their application areas. Their pros and cons are presented in chronological order. We also provide our six‐step generic framework for patient physiological parameters (PPPs) privacy and security in S‐CI: (1) selecting the preliminaries; (2) selecting the system entities; (3) selecting the technique; (4) accessing PPPs; (5) analysing the security; and (6) estimating performance. Meanwhile, we identify and discuss PPPs utilized as datasets and provide the performance evolution of this research area. Finally, we conclude with the open challenges and future directions for this flourishing research area.