Adel Binbusayyis, Abed Alanazi, Shtwai Alsubai, Areej Alasiry, M. Marzougui, Abdullah Alqahtani, Mohemmed Sha, Muhammad Aslam
{"title":"A secured cloud‐medical data sharing with A‐BRSA and Salp ‐Ant Lion Optimisation Algorithm","authors":"Adel Binbusayyis, Abed Alanazi, Shtwai Alsubai, Areej Alasiry, M. Marzougui, Abdullah Alqahtani, Mohemmed Sha, Muhammad Aslam","doi":"10.1049/cit2.12305","DOIUrl":null,"url":null,"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.","PeriodicalId":46211,"journal":{"name":"CAAI Transactions on Intelligence Technology","volume":null,"pages":null},"PeriodicalIF":8.4000,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"CAAI Transactions on Intelligence Technology","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1049/cit2.12305","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
CAAI Transactions on Intelligence Technology is a leading venue for original research on the theoretical and experimental aspects of artificial intelligence technology. We are a fully open access journal co-published by the Institution of Engineering and Technology (IET) and the Chinese Association for Artificial Intelligence (CAAI) providing research which is openly accessible to read and share worldwide.