Privacy-preserving patient monitoring in healthcare IoT using attribute-based cryptography

Mane, Dhiraj Kumar; Deshmukh, Shyam; Durgawale, Prakash M.; Shirkande, Shrinivas T.; Deokate, Sarika T.; Sable, Nilesh P.

doi:10.47974/JDMSC-1896

Open Access Research Article

Privacy-preserving patient monitoring in healthcare IoT using attribute-based cryptography

Dhiraj Kumar Manedhirajmane123@gmail.comKrishna Institute of Medical Sciences Krishna Vishwa Vidyapeeth (Deemed to be University)Krishna Institute of Medical Sciences Krishna Vishwa Vidyapeeth (Deemed to be University) Karad, Maharashtra, 415539, IndiaView full profile → , ^*Shyam DeshmukhCorresponding authordshyam100@yahoo.comDepartment of Information Technology Pune Institute of Computer Technology Savitribai Phule Pune UniversityDepartment of Information Technology Pune Institute of Computer TechnologyPune, Maharashtra, 411043, IndiaView full profile → , Prakash M. Durgawaledrpdurgawale2007@gmail.comDepartment of Community Medicine Krishna Institute of Medical Sciences, (Deemed To Be University)Department of Community Medicine Krishna Institute of Medical Sciences Krishna Vishwa Vidyapeeth (Deemed to be University) Karad, Maharashtra, IndiaView full profile → , Shrinivas T. Shirkandeshri.shirkande8@gmail.comDepartment of Computer Engineering S. B. Patil College of Engineering IndapurPune, Maharashtra, 413106, IndiaView full profile → , Sarika T. Deokatesarikajaankar2017@gmail.comDepartment of Computer Engineering Pimpri Chinchwad College of Engineering NigdiPune, Maharashtra, IndiaView full profile → , Nilesh P. Sabledrsablenilesh@gmail.comDepartment of Computer Science & Engineering (Artificial Intelligence) Bansilal Ramnath Agarwal Charitable Trust’s Vishwakarma Institute of Information TechnologyPune, Maharashtra, IndiaView full profile →

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pp. 513–524Vol. 27Issue 2-AMarch 2024DOI: 10.47974/JDMSC-1896 Crossmark XML

Published Online:: 06 Apr 2024
Article type:: Research Article
Language:: EN
Article no.:: JDMSC-1896
Pages:: 513–524

Abstract

Internet of Things (IoT) technology has revolutionized patient monitoring systems by providing real-time health data for better medical care. However, the rise of IoT devices raises privacy concerns about sensitive health data. This study uses Attribute-based Cryptography (ABC) in patient monitoring to address these concerns. The focus is on adapting attribute detail to IoT device features. Conventional encryption methods often struggle to adapt to IoT devices limited resources, which could compromise patient data privacy. This study suggests a tweak to ABC by adjusting the attribute granularity to better fit the limitations of IoT devices. These resource constraints present challenges, but the methodology proposes an innovative approach to handling and analyzing attributes while protecting patient confidentiality. A dynamic attribute granularity(DAG) model that adapts to IoT device capabilities ensures a data privacy-system performance trade-off in the study. The suggested approach optimizes attribute number and complexity to improve privacy-preserving patient monitoring system scalability and performance. The research thoroughly evaluates the modified ABC-DAG systems data privacy, scalability, and energy efficiency. The results show that the system can protect patient data in a healthcare IoT setting while reducing computational load on low-resource devices. The growing field of privacy-preserving healthcare Internet of Things benefits from this research. It addresses IoT attribute granularity challenges with a customized cryptographic method. The results improve ABC theory in healthcare and provide practical advice for secure and efficient IoT patient monitoring systems.

Keywords

Attribute based cryptography Internet of Things Healthcare Privacy-preserving Patient monitoring

Subject Classifications

Primary 93A30Secondary 49K15

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