A secured cloud-medical data sharing with A-BRSA and Salp -Ant Lion Optimisation Algorithm

Adel Binbusayyis*, Abed Alanazi, Shtwai Alsubai, Areej Alasiry, Mehrez Marzougui, Abdullah Alqahtani, Mohemmed Sha, Muhammad Aslam*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

Sharing medical data among healthcare providers, researchers, and patients is crucial for efficient healthcare services. Cloud-assisted smart healthcare (s-healthcare) systems have made it easier to store EHRs effectively. However, the traditional encryption algorithms used to secure this data can be vulnerable to attacks if the encryption key is compromised, posing a security threat. A secured cloud-based medical data-sharing system is proposed using a hybrid encryption model called A-BRSA, which combines attribute-based encryption (ABE) and B-RSA encryption. The system utilises the Salp-Ant Lion Optimisation Algorithm for optimal key selection. The encrypted data is stored in the cloud and transmitted to the recipient, where it is decrypted using A-BRSA-based decryption. The study measures turnaround time, encryption time, decryption time, and restoration efficiency to evaluate the system's performance. The results demonstrate the effectiveness of the A-BRSA model in ensuring secure medical data sharing in cloud-based s-healthcare systems.

Original languageEnglish
JournalCAAI Transactions on Intelligence Technology
Early online date17 May 2024
DOIs
Publication statusE-pub ahead of print - 17 May 2024

Keywords

  • big data
  • computational intelligence
  • cloud computing
  • computer vision
  • deep learning

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