HIDE-Healthcare IoT data trust management: attribute centric intelligent privacy approach

Ullah, F., Pun, C.-M., Kaiwartya, O. ORCID: 0000-0001-9669-8244, Sadiq, A.S. ORCID: 0000-0002-5746-0257, Lloret, J. and Ali, M., 2023. HIDE-Healthcare IoT data trust management: attribute centric intelligent privacy approach. Future Generation Computer Systems. ISSN 0167-739X

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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.

Item Type: Journal article
Publication Title: Future Generation Computer Systems
Creators: Ullah, F., Pun, C.-M., Kaiwartya, O., Sadiq, A.S., Lloret, J. and Ali, M.
Publisher: Elsevier
Date: 22 June 2023
ISSN: 0167-739X
Divisions: Schools > School of Science and Technology
Record created by: Laura Ward
Date Added: 26 Jun 2023 08:56
Last Modified: 22 Jun 2024 03:00
URI: https://irep.ntu.ac.uk/id/eprint/49265

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