Efficient Joint Key Authentication Model in E-Healthcare

Abstract

Many patients have begun to use mobile applications to handle different health needs because they can better access high-speed Internet and smartphones. These devices and mobile applications are now increasingly used and integrated through the medical Internet of Things (mIoT). mIoT is an important part of the digital transformation of healthcare, because it can introduce new business models and allow efficiency improvements, cost control and improve patient experience. In the mIoT system, when migrating from traditional medical services to electronic medical services, patient protection and privacy are the priorities of each stakeholder. Therefore, it is recommended to use different user authentication and authorization methods to improve security and privacy. In this paper, our prosed model involves a shared identity verification process with different situations in the e-health system. We aim to reduce the strict and formal specification of the joint key authentication model. We use the AVISPA tool to verify through the wellknown HLPSL specification language to develop user authentication and smart card use cases in a user-friendly environment. Our model has economic and strategic advantages for healthcare organizations and healthcare workers. The medical staff can increase their knowledge and ability to analyze medical data more easily. Our model can continuously track health indicators to automatically manage treatments and monitor health data in real time. Further, it can help customers prevent chronic diseases with the enhanced cognitive functions support. The necessity for efficient identity verification in e-health care is even more crucial for cognitive mitigation because we increasingly rely on mIoT systems.

Exploring the Intersection of Geophysics and Diagnostic Imaging in the Health Sciences

“… Image Registration: To register medical pictures from various periods or modalities, geophysical techniques that align and match multiple datasets are used. This aids in monitoring illness development, evaluating therapy effectiveness, and directing interventions [ 127 , 128 ]. …”

“…Medical researchers can make use of the developments achieved in geophysics by modifying and extending computational tools to push the boundaries of medical diagnostics, treatment approaches, and our comprehension of the vast complexity of the human body. This interdisciplinary cooperation enhances diagnostic precision, showcasing the broader implications of technology transfer for advancements in medical research and patient care [ 128 , 129 ].…”

An Intuitionistic Fuzzy based Intelligent System for Semantic Interoperability and Privacy Preservation in Healthcare Systems

“…Access control [22], [23] anonymizing the data [24], [25], authentication [26], [27], and encryption [28] [29] are the primary methods used in healthcare to protect patient privacy. Authentication methods frequently experience man-in-themiddle attacks.…”

“…Sajjad et al [26] suggested a mutual authentication scheme for accessing EHR. They claimed that their protocol has lower computational costs due to a hash function.…”

“…The authors, Aroosa et al [30], pointed out that security is a prime concern in modern healthcare technology in their proposed work on an NDN-based security protocol for IoHT. A solution comprising a combination of public key encryption and homomorphic encryption for keyword search was proposed by [26]. DGHV homomorphic encryption, approximate GCD algorithm, and encrypted inverted Index were their proposed solution's three main building blocks.…”