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Secure cloud storage is an issue of paramount importance that both businesses and end-users should take into consideration before moving their data to, potentially, untrusted clouds. Migrating data to the cloud raises multiple privacy…
Large-scale computational experiments, often running over weeks and over large datasets, are used extensively in fields such as epidemiology, meteorology, computational biology, and healthcare to understand phenomena, and design high-stakes…
The usage of different technologies and smart devices helps people to get medical services remotely for multiple benefits. Thus, critical and sensitive data is exchanged between a user and a doctor. When health data is transmitted over a…
Internet of Things (IoT) devices are capable of allowing for far-reaching access to and evaluation of patient data to monitor health and diagnose from a distance. An electronic healthcare system that checks patient data, prepares medicines…
In an era driven by information exchange, transparency and security hold crucial importance, particularly within the healthcare industry, where data integrity and confidentiality are paramount. This paper investigates the integration of…
The digitization of the medical data has been a sensitive topic. In modern times laws such as the HIPAA provide some guidelines for electronic transactions in medical data to prevent attacks and fraudulent usage of private information. In…
The application of machine learning (ML) algorithms are massively scaling-up due to rapid digitization and emergence of new tecnologies like Internet of Things (IoT). In today's digital era, we can find ML algorithms being applied in the…
Increased collaborative production and dynamic selection of production partners within industry 4.0 manufacturing leads to ever-increasing automatic data exchange between companies. Automatic and unsupervised data exchange creates new…
Verisign reported a 125 percent increase in data breaches within the healthcare sector in the United States during 2022, with 18.2 million patient records being impacted. Growing healthcare data volumes and diversification mean that medical…
Digital healthcare systems are very popular lately, as they provide a variety of helpful means to monitor people's health state as well as to protect people against an unexpected health situation. These systems contain a huge amount of…
This paper introduces a Blockchain-Integrated Explainable AI Framework (BXHF) for healthcare systems to tackle two essential challenges confronting health information networks: safe data exchange and comprehensible AI-driven clinical…
Due to HIPAA and other privacy regulations, it is imperative to maintain patient privacy while conducting research on patient health records. In this paper, we propose AegisBlock, a patient-centric access controlled framework to share…
Secure storage and sharing of patients' medical data over the Internet are part of the challenges for emerging healthcare systems. The use of blockchain technology in medical Internet of things systems can be considered a safe and novel…
Known for its decentralized and tamper-aware properties, blockchain is attractive to enhance the infrastructure of systems that have been constrained by traditionally centralized and vendor-locked environments. Although blockchain has…
Blockchain technology provides a secure and decentralized platform for storing and transferring sensitive medical data, which can be utilized to enable remote medical consultations. This paper proposes a theoretical framework for creating a…
The Internet-of-Things (IoT) is an imminent and corporal technology that enables the connectivity of smart physical devices with virtual objects contriving in distinct platforms with the help of the internet. The IoT is under massive…
The popularization of intelligent healthcare devices and big data analytics significantly boosts the development of smart healthcare networks (SHNs). To enhance the precision of diagnosis, different participants in SHNs share health data…
Wearable fitness devices are widely used to track an individual's health and physical activities to improve the quality of health services. These devices sense a considerable amount of sensitive data processed by a centralized third party.…
A major problem in blockchain-based supply chain management is the potential unreliability of digital twins when considering digital representations of physical goods. Indeed, the use of blockchain technology to trace goods is obviously…
One of the biggest challenges of building artificial intelligence (AI) model in the healthcare area is the data sharing. Since healthcare data is private, sensitive, and heterogeneous, collecting sufficient data for modelling is exhausting,…