Lightweight privacy preservation blockchain framework for healthcare applications using GM-SSO
Data security and privacy are crucial for the Internet of Medical Things (IoMT) and the digitization of healthcare systems. IoMT offers a revolutionary approach to healthcare monitoring, enabling remote patient interaction, sensor data collection, and even in-body implants. However, its wireless nat...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
|
| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S259012302402125X |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841555706885439488 |
|---|---|
| author | Adla Padma Mangayarkarasi Ramaiah |
| author_facet | Adla Padma Mangayarkarasi Ramaiah |
| author_sort | Adla Padma |
| collection | DOAJ |
| description | Data security and privacy are crucial for the Internet of Medical Things (IoMT) and the digitization of healthcare systems. IoMT offers a revolutionary approach to healthcare monitoring, enabling remote patient interaction, sensor data collection, and even in-body implants. However, its wireless nature creates significant security vulnerabilities, and robust security mechanisms are essential to ensure patient trust. Hence, a lightweight privacy preservation mechanism based on blockchain and consensus is developed with minimal computational overhead. Initially, the reputation score is computed for every registered node using the confidence threshold value and transaction to verify the trustworthiness of the IoMT nodes. Tiny Feistel Cipher Encryption technique (TFCEA), a lightweight cryptographic technique, has been proposed to encrypt IoMT data. Based on the computed trust score, an Adaptive Proof of Work (APoW) consensus algorithm has been used to regulate block creation. APoW implements the Genetically Modified Salp Swarm Optimization (GM-SSO) algorithm for the node selection. To make it lightweight, the experimentation used the lightweight cryptographic algorithm and fine-tuned consensus APOW to facilitate the addition of new blocks according to their trust score. In terms of performance analysis, the presented experiments are benchmarked with the well-established works in the candidate domain. Tested results reveal its economic affordability by attaining 243.513 ms for 500 records as an execution time. An informal security analysis has been carried out to justify the robustness of the presented framework against various attacks. To increase resilience against cyber-attacks and ensure reliability in healthcare data security, Modified Principal Component Analysis (MPCA) enabled anomaly detection models were built using the BoT-IoT dataset. Tested models achieve 99.99% and 98.75% accuracy, indicating that the developed model is more suitable to prevent the possible cyber-attacks anticipated in smart healthcare. |
| format | Article |
| id | doaj-art-ce33135b7e214bf29d38b590aa2fd337 |
| institution | Kabale University |
| issn | 2590-1230 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Engineering |
| spelling | doaj-art-ce33135b7e214bf29d38b590aa2fd3372025-01-08T04:53:24ZengElsevierResults in Engineering2590-12302025-03-0125103882Lightweight privacy preservation blockchain framework for healthcare applications using GM-SSOAdla Padma0Mangayarkarasi Ramaiah1School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Vellore 632014, IndiaCorresponding author at: Vellore Institute of Technology, School of Computer Science Engineering and Information systems, Vellore, 632014, Tamil Nadu, India; School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Vellore 632014, IndiaData security and privacy are crucial for the Internet of Medical Things (IoMT) and the digitization of healthcare systems. IoMT offers a revolutionary approach to healthcare monitoring, enabling remote patient interaction, sensor data collection, and even in-body implants. However, its wireless nature creates significant security vulnerabilities, and robust security mechanisms are essential to ensure patient trust. Hence, a lightweight privacy preservation mechanism based on blockchain and consensus is developed with minimal computational overhead. Initially, the reputation score is computed for every registered node using the confidence threshold value and transaction to verify the trustworthiness of the IoMT nodes. Tiny Feistel Cipher Encryption technique (TFCEA), a lightweight cryptographic technique, has been proposed to encrypt IoMT data. Based on the computed trust score, an Adaptive Proof of Work (APoW) consensus algorithm has been used to regulate block creation. APoW implements the Genetically Modified Salp Swarm Optimization (GM-SSO) algorithm for the node selection. To make it lightweight, the experimentation used the lightweight cryptographic algorithm and fine-tuned consensus APOW to facilitate the addition of new blocks according to their trust score. In terms of performance analysis, the presented experiments are benchmarked with the well-established works in the candidate domain. Tested results reveal its economic affordability by attaining 243.513 ms for 500 records as an execution time. An informal security analysis has been carried out to justify the robustness of the presented framework against various attacks. To increase resilience against cyber-attacks and ensure reliability in healthcare data security, Modified Principal Component Analysis (MPCA) enabled anomaly detection models were built using the BoT-IoT dataset. Tested models achieve 99.99% and 98.75% accuracy, indicating that the developed model is more suitable to prevent the possible cyber-attacks anticipated in smart healthcare.http://www.sciencedirect.com/science/article/pii/S259012302402125XPrivacy preservationTrustworthinessLightweight encryptionBlockchainConsensus algorithmAttack mitigation |
| spellingShingle | Adla Padma Mangayarkarasi Ramaiah Lightweight privacy preservation blockchain framework for healthcare applications using GM-SSO Results in Engineering Privacy preservation Trustworthiness Lightweight encryption Blockchain Consensus algorithm Attack mitigation |
| title | Lightweight privacy preservation blockchain framework for healthcare applications using GM-SSO |
| title_full | Lightweight privacy preservation blockchain framework for healthcare applications using GM-SSO |
| title_fullStr | Lightweight privacy preservation blockchain framework for healthcare applications using GM-SSO |
| title_full_unstemmed | Lightweight privacy preservation blockchain framework for healthcare applications using GM-SSO |
| title_short | Lightweight privacy preservation blockchain framework for healthcare applications using GM-SSO |
| title_sort | lightweight privacy preservation blockchain framework for healthcare applications using gm sso |
| topic | Privacy preservation Trustworthiness Lightweight encryption Blockchain Consensus algorithm Attack mitigation |
| url | http://www.sciencedirect.com/science/article/pii/S259012302402125X |
| work_keys_str_mv | AT adlapadma lightweightprivacypreservationblockchainframeworkforhealthcareapplicationsusinggmsso AT mangayarkarasiramaiah lightweightprivacypreservationblockchainframeworkforhealthcareapplicationsusinggmsso |