Secure Data Collection and Encryption of Medical Data in Cloud Storage for Healthcare Systems

Healthcare organizations are dealing with a vast amount of medical data that demands well-known and trustworthy data management techniques. The paper outlines a holistic framework for secure collection, encryption and storage of patient medical data in Cloud computing scenarios. The method implements the concepts of secure multi-party computation (SMPC) to encrypt the data kept in the healthcare database, to guarantee individual privacy and confidentiality, and utilises Transport Layer Security (TLS) to guarantee the safety of information transfer. The data is decrypted and distributed over multiple cloud servers to keep the data redundant and available across all of them as well as availability for fault tolerance. System is assessed with detailed comparisons of the time taken to generate keys, time needed to encrypt and cloud computing based values. The results demonstrate that the RSA-4096 encryption algorithm has a much longer key generation time of around 1.4 s, whereas the proposed encryption method has a key generation time of 0.6 s. In terms of encryption times, ChaCha20 was the fastest at around 0 s, followed by the proposed algorithm at 0.2 s, and then RSA-4096 at 0.6 s. Further, the effectiveness of the system was established about cloud computing performance parameters based on disk I/O (from 40 MB/s to 200 MB/s), CPU usage (65–200%), response times (50 ms–200 ms), and throughput (50–200 req/s). This clearly shows that the methodology proposed offers efficient and secure management for healthcare data in cloud environments with a good balance between security and performance.

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Publication Details

Journal
Artificial Intelligence and Emerging Technologies
Published
2026-06-30
DOI
https://doi.org/10.53941/aiet.2026.100006
Primary Topic
Cloud Data Security Solutions
Type
article
Field-Weighted Citation Impact
0.00
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article

Secure Data Collection and Encryption of Medical Data in Cloud Storage for Healthcare Systems

Sri Harsha Grandhi, Akhil Raj Gaius Yallamelli, Bhanutheja Nagabhushana Reddy Kasinayakanahally, Rudhrananth Baladhandapani et al.
Artificial Intelligence and Emerging Technologies
Cloud Data Security Solutions
article

Secure Data Collection and Encryption of Medical Data in Cloud Storage for Healthcare Systems

Sri Harsha Grandhi, Akhil Raj Gaius Yallamelli, Bhanutheja Nagabhushana Reddy Kasinayakanahally, Rudhrananth Baladhandapani, Soundarraj K.
article en

Abstract

Healthcare organizations are dealing with a vast amount of medical data that demands well-known and trustworthy data management techniques. The paper outlines a holistic framework for secure collection, encryption and storage of patient medical data in Cloud computing scenarios. The method implements the concepts of secure multi-party computation (SMPC) to encrypt the data kept in the healthcare database, to guarantee individual privacy and confidentiality, and utilises Transport Layer Security (TLS) to guarantee the safety of information transfer. The data is decrypted and distributed over multiple cloud servers to keep the data redundant and available across all of them as well as availability for fault tolerance. System is assessed with detailed comparisons of the time taken to generate keys, time needed to encrypt and cloud computing based values. The results demonstrate that the RSA-4096 encryption algorithm has a much longer key generation time of around 1.4 s, whereas the proposed encryption method has a key generation time of 0.6 s. In terms of encryption times, ChaCha20 was the fastest at around 0 s, followed by the proposed algorithm at 0.2 s, and then RSA-4096 at 0.6 s. Further, the effectiveness of the system was established about cloud computing performance parameters based on disk I/O (from 40 MB/s to 200 MB/s), CPU usage (65–200%), response times (50 ms–200 ms), and throughput (50–200 req/s). This clearly shows that the methodology proposed offers efficient and secure management for healthcare data in cloud environments with a good balance between security and performance.

Artificial Intelligence and Emerging TechnologiesVol. 3(2)
Apple (Israel) (IL), Amazon (United States) (US), Save Ourselves Breast Cancer Organization (US), Ramakrishna Mission Vidyalaya (IN), Apple (United States) (US)
Openalex Percentile: Top 4%
Cloud Data Security Solutions
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