Title: Securing healthcare in the cloud: a machine learning perspective

Authors: Suneeta Satpathy; Subhasish Mohapatra; Pratik Kumar Swain; Bijay Kumar Paikaray

Addresses: Department of Computer Science and Engineering, Center for AI and ML, Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, Odisha, India ' Department of CSE, Adamas University, Kolkata, India ' Faculty in Emerging Technologies, Sri Sri University, Cuttack, India ' Department of Computer Science and Engineering, Centre for Data Science, Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, Odisha, India

Abstract: The healthcare sector has transformed because of cloud computing, which provides scalable and affordable methods for handling and storing enormous volumes of patient data. However, ensuring the security and privacy of sensitive healthcare information remains a significant challenge. This paper explores the application of machine learning techniques to enhance the security of cloud healthcare services. The study discusses the potential benefits of machine learning in detecting and preventing security breaches, and ensuring data privacy, and addresses the unique challenges faced by the healthcare industry in cloud computing. The present research adopts different machine learning algorithms that can be leveraged to strengthen the security of cloud healthcare services and present real-world examples of their implementation. Finally, the paper discusses the limitations and future directions of the application of machine learning in securing cloud healthcare services.

Keywords: cloud healthcare system; machine learning; web services; security.

DOI: 10.1504/IJIMS.2025.146819

International Journal of Internet Manufacturing and Services, 2025 Vol.11 No.2, pp.114 - 131

Received: 27 Jan 2024
Accepted: 22 Mar 2024
Published online: 20 Jun 2025 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article