Multimedia data processing in an intelligent medical system featuring embedded elliptic curve cryptography

Abdullaeva, Turaeva, Yadgarova, Khalimova, Eshonkulova, Yormatova and Nazarov

Health Leadership and Quality of Life, 2024, vol. 3, .199

Abstract: Currently, global disease diagnosis is prevalent, and the evaluation of digital medical images (MI) is integral to Intelligent Medical Systems (IMS), which facilitates the early diagnosis and treatment of prevalent and severe illnesses. In this scenario, modifying or altering just one pixel of an MI during transmission across an insecure channel might result in an erroneous diagnosis, jeopardizing patient health and causing detrimental delays. Consequently, transmitting IMS multimedia information to healthcare providers presents several security issues. This study presents a Multimedia Data Processing framework using Embedded Elliptic Curve Cryptography (MDP-EECC) inside an IMS. The suggested MDP architecture comprises an Edge Level (EL), a Fog Computing (FC) stage, a Cloud computing Storage (CS) level, and a Blockchain (BC) tier. The EL gathers and transmits regular health data from the patient to the upper layer. The multimedia information from the EL is safely stored in BC-assisted CS via FC nodes using simple cryptography. Medical professionals conduct secure searches of such data for therapy or monitoring purposes. Inexpensive cryptographic methods are suggested via the use of Elliptic Curve Cryptography (ECC) with ECC-Diffie-Hellman (ECDH) and ECC-Digital Signature (ECDS) algorithms to ensure the security of MDP while preserving privacy. The suggested approach is tested using publicly accessible chest X-ray pictures. The efficacy of the suggested version is assessed and validated via comprehensive experimentation using the latest security techniques available. Compared to state-of-the-art approaches, the suggested version demonstrates superior security characteristics and can withstand different known assaults.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:dbk:health:v:3:y:2024:i::p:.199:id:.199

DOI: 10.56294/hl2024.199

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