A Blockchain-enabled Intelligent Electronic Healthcare Platform

Healthcare frameworks have evolved over the decades with the advancements in technology. Patient disease prevention, diagnosis, treatment, and well-being in general have progressed tremendously with the support of Artificial Intelligence (AI), data science, and advances in networking and communication. The security of the healthcare system plays an important role in the robustness and integrity of patient healthcare records. The use of intrusion detection and prevention plays a pivotal role in securing not only healthcare systems but also electronic health records. Today, traditional healthcare security frameworks that rely on conventional Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS) cannot cope with the vulnerability of complex cyber attacks that can jeopardize private patient information. Furthermore, healthcare frameworks are shifting towards distributed and decentralized architectures that conventional IDS and IPS solutions are incapable of protecting. With that said, in this paper we present a blockchain-enabled IDS framework to protect electronic healthcare systems, which uses a diversified set of centralized, distributed, and decentralized security measures to detect and prevent a plethora of cyber attacks. The system is designed to be adaptable and capable of finding new and developing threats. A data set is simulated on the basis of healthcare flows, access levels, and reason. The evaluation results show that the proposed IDS framework provides adequate results in improving security.

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Publication Details

Published
2024-11-26
DOI
https://doi.org/10.1109/bcca62388.2024.10844466
Citations
2
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.49
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article

A Blockchain-enabled Intelligent Electronic Healthcare Platform

Muder Almiani, Ismaeel Al Ridhawi, Ali Abbas, Akshay Agrawal
2 citations
Brain Tumor Detection and Classification
0.49
article

A Blockchain-enabled Intelligent Electronic Healthcare Platform

Muder Almiani, Ismaeel Al Ridhawi, Ali Abbas, Akshay Agrawal
article en
2 citations

Abstract

Healthcare frameworks have evolved over the decades with the advancements in technology. Patient disease prevention, diagnosis, treatment, and well-being in general have progressed tremendously with the support of Artificial Intelligence (AI), data science, and advances in networking and communication. The security of the healthcare system plays an important role in the robustness and integrity of patient healthcare records. The use of intrusion detection and prevention plays a pivotal role in securing not only healthcare systems but also electronic health records. Today, traditional healthcare security frameworks that rely on conventional Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS) cannot cope with the vulnerability of complex cyber attacks that can jeopardize private patient information. Furthermore, healthcare frameworks are shifting towards distributed and decentralized architectures that conventional IDS and IPS solutions are incapable of protecting. With that said, in this paper we present a blockchain-enabled IDS framework to protect electronic healthcare systems, which uses a diversified set of centralized, distributed, and decentralized security measures to detect and prevent a plethora of cyber attacks. The system is designed to be adaptable and capable of finding new and developing threats. A data set is simulated on the basis of healthcare flows, access levels, and reason. The evaluation results show that the proposed IDS framework provides adequate results in improving security.

University of Ottawa (CA), Gulf University for Science & Technology (KW), Kuwait College of Science and Technology (KW)
Industry, innovation and infrastructure
Openalex Percentile: Top 31%
Brain Tumor Detection and Classification
0.49
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A Blockchain-enabled Intelligent Electronic Healthcare Platform — Muder Almiani, Ismaeel Al Ridhawi, et al. · (2024) | TGRS Research Map | TGRS