Mohammad Gouse Galety
title
Medical data security and effective organization using integrated Blockchain principles in AI-based healthcare 6.0 infrastructures
Abstract
The future industry development for healthcare services needs an integrated edge, fog, and cloud computing infrastructures. The medical data security and integrity schemes help to operate the data carefully in healthcare networks. The research on HC-6.0 deals with hospital management, blockchain-based data security, and Artificial Intelligence (AI)-based medical data analysis solutions. However, conventional blockchain principles and AI-based industry solutions are vulnerable to attacks and real-time complexities. The drawbacks of current healthcare industry attainments on HC-6.0 include limited flexibility in data interoperability, multi-dimensional blockchain construction, and efficient data diagnosis principles. Blockchain technology requires future-ready solutions with AI functions. Medical data interoperability among different computing platforms needs intelligent security options. Moreover, adapting conventional blockchain network principles in healthcare platforms is unsuitable due to single-root Merkle tree structures. On the scope, the proposed Intelligent and Secure Medical Data Interoperability (ISMDI) system has been developed using integrated blockchain constructions. To attain more organized data operations, security benefits, data interoperability, and confidentiality, the ISMDI system inducts novel procedures for establishing efficient HC-6.0 infrastructures. The internal procedures of the ISMDI system include Multi-Sensor Data Collection, Deep Contractive Auto Encoder (CAE)-based Reduction, Edge-Level Merkle Tree Formation, Multi-Level Blockchain Construction, Edge Coordinated Blockchain Tree at Fog Computing Centre Point, and Fog-based Secure and Distributed Sensor Data Analysis functions (Bidirectional Long Short Term Memory (BLSTM)). The article justifies the successful implementation of the ISMDI procedures, stating that the performance of the proposed model provides 12% to 16% better results than the existing healthcare schemes.
Biography
Mohammad Gouse Galety, a seasoned professional in computer science, is currently the dean and professor at the School of Computing at Samarkand International University of Technology, Samarkand, Uzbekistan. His research interests encompass a wide range of computer and information science, focusing on Web Mining, Computer Vision, IoT, Machine Learning, and Artificial Intelligence. His impactful research has led to the (co) authorship of several journal papers and international conference proceedings indexed by Springer, Web of Science, and Scopus, holding four patents, and writing six books. His standing in the academic community is further solidified by his role as a Fellow of the IEEE and ACM.
With a career spanning over two decades, Mohammad Gouse Galety has served in many national and international organizations, solidifying his expertise in the field. His teaching experience includes roles at Sree Vidyanikethan Degree College, India; Emeralds Degree College, Tirupati, India; Brindavan College of Engineering, India; Kuwait Educational Center, Kuwait; Ambo University, Ethiopia; Debre Berhan University, Ethiopia; Lebanese French University, Iraq; and Catholic University in Erbil, Iraq. He imparts his knowledge to undergraduate and postgraduate students, teaching various courses in computer science and information technology/science engineering.