RBEF: Ransomware Efficient Public Blockchain Framework for Digital Healthcare Application

Author:

Lakhan Abdullah1ORCID,Thinnukool Orawit2ORCID,Groenli Tor Morten1ORCID,Khuwuthyakorn Pattaraporn34ORCID

Affiliation:

1. School of Economics, Innovation and Technology, and Kristiania University College, 0107 Oslo, Norway

2. Embedded System and Computational Science, College of Arts, Media and Technology, Chiang Mai University, Chiang Mai 50200, Thailand

3. RSISE, Australian National University, Canberra, ACT 0200, Australia

4. College of Arts and Technology, Chiang Mai University, Chiang Mai 50200, Thailand

Abstract

These days, the use of digital healthcare has been growing in practice. Getting remote healthcare services without going to the hospital for essential checkups and reports is easy. It is a cost-saving and time-saving process. However, digital healthcare systems are suffering from security and cyberattacks in practice. Blockchain technology is a promising technology that can process valid and secure remote healthcare data among different clinics. However, ransomware attacks are still complex holes in blockchain technology and prevent many healthcare data transactions during the process on the network. The study presents the new ransomware blockchain efficient framework (RBEF) for digital networks, which can identify transaction ransomware attacks. The objective is to minimize transaction delays and processing costs during ransomware attack detection and processing. The RBEF is designed based on Kotlin, Android, Java, and socket programming on the remote process call. RBEF integrated the cuckoo sandbox static and dynamic analysis application programming interface (API) to handle compile-time and runtime ransomware attacks in digital healthcare networks. Therefore, code-, data-, and service-level ransomware attacks are to be detected in blockchain technology (RBEF). The simulation results show that the RBEF minimizes transaction delays between 4 and 10 min and processing costs by 10% for healthcare data compared to existing public and ransomware efficient blockchain technologies healthcare systems.

Funder

Program Management Unit for Human Resources and Institutional Development, Research and Innovation

Kristiania University College and Chiang Mai University

research group of Embedded System and Computational Science, Chiang Mai University

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

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