ItemArticle

A Novel Blockchain-Integrated Deep Learning Framework for Securing Smart Healthcare Communication Networks

Title
A Novel Blockchain-Integrated Deep Learning Framework for Securing Smart Healthcare Communication Networks
Creator
Malik, Rohit; Dua, Sakshi; Shoran, Preety; Upreti, Kamal
Description
With the rapid expansion of intelligent medical equipment and their interconnectedness through the Internet of Things (IoT), addressing safety issues in the communicating system has become increasingly critical. A learning mechanism is proposed for an intelligent healthcare-based communication system that uses blockchain for secure network communication and incorporates a data evaluation layer based on cloud which actively segregates and ranks transactions into three main categories: Good, Moderate, and Malware. Fog servers are utilized to route the communicating nodes via Rician and Rayleigh channels. The learning mechanism employs a deep neural network to instruct and classify categories, thereby improving the blockchain layer's decision-making process. This paper introduces several significant contributions, such as the development of a secure blockchain framework for user authentication and a protected digital ledger for communication. Additionally, it incorporates a cloud-driven data analysis layer combined with a neural network to improve training accuracy and category classification. The developed algorithm surpassed the existing works in terms of quality of service (QoS) parameters with low latency, bit error rate (BER), higher signal to inference plus noise ratio (SINR), packet delivery ratio (PDR), true detection rate (TDR), false detection rate (FDR), and throughput. Also, a thorough comparison of consensus mechanisms like practical Byzantine fault tolerance (pBFT), proof of work (PoW), Raft, and Paxos is done to ensure which consensus helps optimize the proposed system in terms of security and fault tolerance with low latency and energy-efficient operations. It also establishes a secure and efficient communication network for smart healthcare, aimed at enhancing the overall quality of life for individuals. 2025 Wiley Periodicals LLC.
Source
Computational Intelligence;Volume;41;Issue;6;Article No.;e70132;
Date
01-01-2025
Publisher
John Wiley and Sons Inc
Subject
blockchain technology; consensus mechanisms; fog computing; IoT security; neural network classification; smart healthcare communication
Coverage
Malik R., School of Computer Applications, Lovely Professional University, Punjab, Phagwara, India; Dua S., School of Computer Applications, Lovely Professional University, Punjab, Phagwara, India; Shoran P., School of Sciences, Christ University, Uttar Pradesh, Ghaziabad, India; Upreti K., School of Sciences, Christ University, Uttar Pradesh, Ghaziabad, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISSN: 8247935; CODEN: COMIE
Format
online
Language
English
Type
Article

Citation

Malik, Rohit; Dua, Sakshi; Shoran, Preety; Upreti, Kamal, “A Novel Blockchain-Integrated Deep Learning Framework for Securing Smart Healthcare Communication Networks,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 20, 2026, https://archives.christuniversity.in/items/show/22970.

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