ItemArticle

An enhanced hybrid framework for IoT healthcare security using blockchain-driven multimedia data analysis and cybersecurity techniques

Title
An enhanced hybrid framework for IoT healthcare security using blockchain-driven multimedia data analysis and cybersecurity techniques
Creator
Parashar, Jyoti; Hung, Bui Thanh; Upreti, Kamal; Kshirsagar, Pravin R.; Mahajan, Shubham; Kadry, Seifedine
Description
In the era of digital healthcare, safeguarding sensitive patient information while ensuring real-time access and decision-making is paramount. This study presents a novel Hybrid Blockchain-IoT Framework for secure healthcare data management, integrating Elman neural networkbased Blowfish encryption with blockchain and deep anomaly detection. The framework leverages IoT sensor data and utilizes a Proof-of-Authority (PoA) consensus mechanism to ensure tamper-proof transaction recording across decentralized nodes. A Long Short-Term Memory (LSTM) autoencoder combined with a Support Vector Machine (SVM) classifier enables accurate anomaly detection, while cryptographic functions ensure privacy and data integrity. The proposed system is evaluated using a healthcare dataset comprising over 1000 patient records across three network configurations (195, 585, and 1171 nodes). Results demonstrate a Wormhole Attack Probability (%) as low as 1.1%, Product Drop Ratio (%) between 1.2 and 2.7%, and Authentication Delay under 111 msoutperforming existing systems. Although the anomaly detection accuracy (98.98%) and F1-Score (0.90) are slightly below leading deep learning models, our framework uniquely combines encrypted transmission, distributed validation, and intelligent threat detection in a practical healthcare setting. The architecture ensures security, scalability, and efficiency, positioning it as a robust solution for next-generation smart healthcare ecosystems. 2026 The Authors
Source
Array;Volume;30;Issue;;Article No.;100759;
Date
01-01-2026
Publisher
Elsevier B.V.
Subject
Blockchain technology; Data management; IOT; Privacy; Security; Smart healthcare
Coverage
Parashar J., Department of Computer Science and Engineering, Panipat Institute of Engineering and Technology (PIET), Haryana, India; Hung B.T., Data Science Laboratory, Data Science Department, Faculty of Information Technology, Industrial University of Ho Chi Minh City, Viet Nam; Upreti K., Department of Computer Science, CHRIST (Deemed to be University), Delhi NCR Campus, Ghaziabad, India; Kshirsagar P.R., Department of Electronics & Telecommunication Engineering, J D College of Engineering & Management, Maharashtra, Nagpur, India; Mahajan S., Amity School of Engineering & Technology, Amity University, Haryana, India; Kadry S., Department of Computer Science and Mathematics, Lebanese American University, Beirut, Lebanon
Rights
All Open Access; Gold Open Access
Relation
ISSN: 25900056;
Format
online
Language
English
Type
Article

Citation

Parashar, Jyoti; Hung, Bui Thanh; Upreti, Kamal; Kshirsagar, Pravin R.; Mahajan, Shubham; Kadry, Seifedine, “An enhanced hybrid framework for IoT healthcare security using blockchain-driven multimedia data analysis and cybersecurity techniques,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 19, 2026, https://archives.christuniversity.in/items/show/22198.

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