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HIDE-Healthcare IoT Data Trust ManagEment: Attribute centric intelligent privacy approach
Fasee Ullah1,2; Chi-Man Pun1; Omprakash Kaiwartya3; Ali Safaa Sadiq3; Jaime Lloret4; Mohammed Ali5
2023-06-22
Source PublicationFuture Generation Computer Systems
ISSN0167-739X
Volume148Pages:326-341
Abstract

The cloud-based Internet of Things (IoTs) storage enables patients to monitor their health remotely and offers services for physicians of various Medical Institutions (MIs) to diagnose and treat them on time. As a matter of trust, patients are legally expected to hide their real identity and ensure data privacy in the cross-domain of IoT-healthcare, whether it is stored correctly or modified due to external and internal attacks in the cloud. Additionally, physicians treat patients and continuously store duplicated data in cloud storage, which increases the cost of computing. In this context, this paper presents HIDE-Healthcare IoT Data privacy trust management framework, focusing on attributes. Patients’ attributes are used to encrypt and decrypt sensory data between patients and different entities by incorporating the idea of trustworthy and secure shared keys. HIDE uses an intelligent object's pointer to store the same patient's sensory data in various versions to prevent data duplication, which will help track MIs that treat patients. An intelligent content-based emergency data access control is developed to monitor multiple patient health criticalities in HIDE. The security analysis and experimental evaluation attest to the benefits of the proposed HIDE framework, considering security and privacy metrics.

KeywordHealthcare Intelligence Internet Of Things Privacy Security Trust
DOI10.1016/j.future.2023.05.008
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaComputer Science
WOS SubjectComputer Science, Theory & Methods
WOS IDWOS:001035240300001
PublisherELSEVIERRADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
Scopus ID2-s2.0-85163873137
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Citation statistics
Document TypeJournal article
CollectionFaculty of Science and Technology
DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorJaime Lloret
Affiliation1.University of Macau,Taipa,Avenida da Universidade,Macao
2.Department of Computer Science & IT,Sarhad Univesity of Science & IT,Peshawar,Pakistan
3.Department of Computer Science,Nottingham Trent University,Clifton,Clifton Lane, Nottingham,NG11 8NS,United Kingdom
4.Instituto de Investigación para la gestión Integrada de Zonas Costeras,Universitat Politécnica de Valencia,Valencia,Camino Vera s/n,46022,Spain
5.Department of Computer Science,King Khalid University,Abha,61421,Saudi Arabia
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Fasee Ullah,Chi-Man Pun,Omprakash Kaiwartya,et al. HIDE-Healthcare IoT Data Trust ManagEment: Attribute centric intelligent privacy approach[J]. Future Generation Computer Systems, 2023, 148, 326-341.
APA Fasee Ullah., Chi-Man Pun., Omprakash Kaiwartya., Ali Safaa Sadiq., Jaime Lloret., & Mohammed Ali (2023). HIDE-Healthcare IoT Data Trust ManagEment: Attribute centric intelligent privacy approach. Future Generation Computer Systems, 148, 326-341.
MLA Fasee Ullah,et al."HIDE-Healthcare IoT Data Trust ManagEment: Attribute centric intelligent privacy approach".Future Generation Computer Systems 148(2023):326-341.
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