Abstract
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.
Highlights
The advancement and application of Wireless Body Area Networks (WBANs) are considered key research areas for improving healthcare quality [1]
This study has provided a detailed literature review of patient data privacy and security in sensor-cloud infrastructure (S-CI)
We can clearly see that many techniques are proposed for mobile healthcare and e-healthcare and that there is much scope in the areas of research into health data management and health data aggregation
Summary
The advancement and application of Wireless Body Area Networks (WBANs) are considered key research areas for improving healthcare quality [1]. Pervasive healthcare monitoring provides rich contextual information to handle the odd conditions of chronically ill patients. Constant monitoring and an early medical response increase the life quality of elderly and chronically ill people and help families and parents by providing high-quality healthcare to their young babies and paralyzed children [1,2,3,4,5,6]. Some WBANs are dedicated to continuous observation of cognitive diseases such as Alzheimer’s, epilepsy, and Parkinson’s disease. Another significant advancement in WBANs is the formation of tiny sensors implanted in the human body or integrated into fabric
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