International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

Frequency: 12
line decor
  
line decor

 Volume 12, Issue 2 (February 2025), Pages: 52-61

----------------------------------------------

 Review Paper

Secure e-health framework using artificial intelligence and blockchain technology

 Author(s): 

 Reham Almukhlifi 1, Mahmoud Ahmad Al-Khasawneh 2, 3, *, Amal Abdullah Bukhari 4, Ahmad Ali Ahmad Harasis 5

 Affiliation(s):

 1Department of Computer Science, College of Computer Science and Engineering, Taibah University, Medina 42353, Saudi Arabia
 2School of Computing, Skyline University College, University City Sharjah, 1797, Sharjah, UAE
 3Applied Science Research Center, Applied Science Private University, Amman, Jordan
 4College of Computer Science and Engineering, University of Jeddah, Jeddah, Saudi Arabia
 5Business Management Department, Faculty of Business, Middle East University, Amman, Jordan

 Full text

  Full Text - PDF

 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0003-1698-0237

 Digital Object Identifier (DOI)

 https://doi.org/10.21833/ijaas.2025.02.006

 Abstract

This review explores emerging technologies in the healthcare sector, specifically focusing on blockchain and artificial intelligence (AI). Data on healthcare trends were gathered from documents published on the Web of Sciences and various Google surveys conducted by different governing bodies. The review aims to examine the potential of integrating blockchain and AI to enhance healthcare by promoting the use of generalizable analytical technologies that can be integrated into comprehensive risk management strategies. This article discusses how blockchain can be utilized as an open network for sharing and authorizing information, which creates opportunities for developing reliable AI models for e-health. AI, using various algorithms and decision-making capabilities, can help healthcare professionals access patient medical records stored on the blockchain. This integration is expected to improve the efficiency of the medical system, reduce costs, and democratize healthcare delivery by incorporating the latest technological advances. Cryptographic records stored on blockchains are essential for AI to securely manage information. The main goal of this article is to develop a secure e-health framework using AI and blockchain technology, referred to as SEHFUAIBC. The design science methodology (DSM) was used in this study. The SEHFUAIBC framework includes seven components: advanced encryption algorithms, access control, multi-factor authentication, AI-based threat detection, blockchain-based data sharing, privacy protection, and audit trail. The framework was evaluated using real-world scenarios, and the results show that the combination of AI and blockchain in this framework provides hybrid security techniques that are crucial for protecting e-health records from unauthorized access.

 © 2025 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords

 Blockchain technology, Artificial intelligence, E-health framework, Healthcare efficiency, Data security

 Article history

 Received 17 May 2024, Received in revised form 3 November 2024, Accepted 19 January 2025

 Acknowledgment

No Acknowledgment.

 Compliance with ethical standards

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Almukhlifi R, Al-Khasawneh MA, Bukhari AA, and Harasis AAA (2025). Secure e-health framework using artificial intelligence and blockchain technology. International Journal of Advanced and Applied Sciences, 12(2): 52-61

 Permanent Link to this page

 Figures

 Fig. 1 Fig. 2 Fig. 3 Fig. 4 

 Tables

 Table 1

----------------------------------------------   

 References (34)

  1. Agu PC and Obulose CN (2024). Piquing artificial intelligence towards drug discovery: Tools, techniques, and applications. Drug Development Research, 85(2): e22159. https://doi.org/10.1002/ddr.22159   [Google Scholar] PMid:38375772
  2. Akkiraju R, Sinha V, Xu A, Mahmud J, Gundecha P, Liu Z, Liu X, and Schumacher J (2020). Characterizing machine learning processes: A maturity framework. In the Business Process Management: 18th International Conference, Springer International Publishing, Seville, Spain: 17-31. https://doi.org/10.1007/978-3-030-58666-9_2   [Google Scholar]
  3. Alabdulatif A, Al Asqah M, Moulahi T, and Zidi S (2023). Leveraging artificial intelligence in blockchain-based e-health for safer decision making framework. Applied Sciences, 13(2): 1035. https://doi.org/10.3390/app13021035   [Google Scholar]
  4. Al-Dhaqm A, Abd Razak S, Dampier DA, Choo KK, Siddique K, Ikuesan RA, Alqarni A, and Kebande VR (2020). Categorization and organization of database forensic investigation processes. IEEE Access, 8: 112846-112858. https://doi.org/10.1109/ACCESS.2020.3000747   [Google Scholar]
  5. Alotaibe DZ (2024). IoT security model for smart cities based on a metamodeling approach. Engineering, Technology and Applied Science Research, 14(3): 14109-14118. https://doi.org/10.48084/etasr.7132   [Google Scholar]
  6. Alotaibi F, Al-Dhaqm A, and Al-Otaibi YD (2023). A conceptual digital forensic investigation model applicable to the drone forensics field. Engineering, Technology and Applied Science Research, 13(5): 11608-11615. https://doi.org/10.48084/etasr.6195   [Google Scholar]
  7. Alotaibi YK and Federico F (2017). The impact of health information technology on patient safety. Saudi Medical Journal, 38(12): 1173-1180. https://doi.org/10.15537/smj.2017.12.20631   [Google Scholar] PMid:29209664 PMCid:PMC5787626
  8. Alotibi G (2024). A cybersecurity awareness model for the protection of Saudi students from social media attacks. Engineering, Technology and Applied Science Research, 14(2): 13787-13795. https://doi.org/10.48084/etasr.7123   [Google Scholar]
  9. Bragazzi NL, Dai H, Damiani G, Behzadifar M, Martini M, and Wu J (2020). How big data and artificial intelligence can help better manage the COVID-19 pandemic. International Journal of Environmental Research and Public Health, 17(9): 3176. https://doi.org/10.3390/ijerph17093176   [Google Scholar] PMid:32370204 PMCid:PMC7246824
  10. Campanella P, Lovato E, Marone C, Fallacara L, Mancuso A, Ricciardi W, and Specchia ML (2016). The impact of electronic health records on healthcare quality: A systematic review and meta-analysis. The European Journal of Public Health, 26(1): 60-64. https://doi.org/10.1093/eurpub/ckv122   [Google Scholar] PMid:26136462
  11. Chakraborty S, Aich S, and Kim HC (2019). A secure healthcare system design framework using blockchain technology. In the 21st International Conference on Advanced Communication Technology, IEEE, PyeongChang, Korea: 260-264. https://doi.org/10.23919/ICACT.2019.8701983   [Google Scholar]
  12. Chapuis C, Roustit M, Bal G, Schwebel C, Pansu P, David-Tchouda S, Foroni L, Calop J, Timsit JF, Allenet B, and Bosson JL et al. (2010). Automated drug dispensing system reduces medication errors in an intensive care setting. Critical Care Medicine, 38(12): 2275-2281. https://doi.org/10.1097/CCM.0b013e3181f8569b   [Google Scholar] PMid:20838333
  13. Farhadighalati N, Ghalaty NF, Nikghadam-Hojjati S, Marchetti E, and Barata J (2023). SAFE-HEALTH: A secure framework for advancing edge-based health 5.0. In the IEEE 9th World Forum on Internet of Things, IEEE, Aveiro, Portugal: 1-6. https://doi.org/10.1109/WF-IoT58464.2023.10539418   [Google Scholar]
  14. Gayathri N, Sakthivel RK, Rizwan P, Gandomi AH, Muthuramalingam S, and Balamurugan B (2020). Securing e-health records using keyless signature infrastructure blockchain technology in the cloud. Neural Computing and Applications, 32(3): 639-647. https://doi.org/10.1007/s00521-018-3915-1   [Google Scholar]
  15. Ghazal TM, Hasan MK, Abdullah SNHS, Bakar KAA, and Al Hamadi H (2022). Private blockchain-based encryption framework using computational intelligence approach. Egyptian Informatics Journal, 23(4): 69-75. https://doi.org/10.1016/j.eij.2022.06.007   [Google Scholar]
  16. Jakhar AK, Singh M, Sharma R, Viriyasitavat W, Dhiman G, and Goel S (2024). A blockchain-based privacy-preserving and access-control framework for electronic health records management. Multimedia Tools and Applications, 83: 84195–84229. https://doi.org/10.1007/s11042-024-18827-3   [Google Scholar]
  17. Jennath HS, Anoop VS, and Asharaf S (2020). Blockchain for healthcare: Securing patient data and enabling trusted artificial intelligence. International Journal of Interactive Multimedia and Artificial Intelligence, 6(3): 15-23. https://doi.org/10.9781/ijimai.2020.07.002   [Google Scholar]
  18. Kubendiran M, Singh S, and Sangaiah AK (2019). Enhanced security framework for e-health systems using blockchain. Journal of Information Processing Systems, 15(2): 239-250.   [Google Scholar]
  19. Kumar P, Kumar R, Garg S, Kaur K, Zhang Y, and Guizani M (2022). A secure data dissemination scheme for IoT-based e-health systems using AI and blockchain. In the GLOBECOM 2022-2022 IEEE Global Communications Conference, IEEE, Rio de Janeiro, Brazil: 1397-1403. https://doi.org/10.1109/GLOBECOM48099.2022.10000801   [Google Scholar]
  20. Mak KK, Wong YH, and Pichika MR (2023). Artificial intelligence in drug discovery and development. In: Hock FJ and Pugsley MK (Eds.), Drug discovery and evaluation: Safety and pharmacokinetic assays: 1-38. Springer, Cham, Switzerland. https://doi.org/10.1007/978-3-030-73317-9_92-1   [Google Scholar]
  21. Mallikarjuna B, Kiranmayee D, Saritha V, and Krishna PV (2021). Development of efficient e-health records using IoT and blockchain technology. In the ICC 2021-IEEE International Conference on Communications, IEEE, Montreal, Canada: 1-7. https://doi.org/10.1109/ICC42927.2021.9500390   [Google Scholar]
  22. March ST and Smith GF (1995). Design and natural science research on information technology. Decision support systems, 15(4): 251-266. https://doi.org/10.1016/0167-9236(94)00041-2   [Google Scholar]
  23. Mourya AK, Kapil G, and Idrees SM (2024). Modernizing healthcare data management: A fusion of mobile agents and blockchain technology. In: Idrees SM and Nowostawski M (Eds.), Blockchain transformations: Navigating the decentralized protocols era: 93-106. Springer Nature, Cham, Switzerland. https://doi.org/10.1007/978-3-031-49593-9_6   [Google Scholar]
  24. Priyanka EB, Thangavel S, Mohanasundaram R, and Subramaniam S (2024). Artificial intelligence approaches in healthcare informatics toward advanced computation and analysis. The Open Biomedical Engineering Journal, 18: e18741207281491. https://doi.org/10.2174/0118741207281491240118060019   [Google Scholar]
  25. Quasim MT, Radwan AAE, Alshmrani GMM, and Meraj M (2020). A blockchain framework for secure electronic health records in healthcare industry. In the International Conference on Smart Technologies in Computing, Electrical and Electronics, IEEE, Bengaluru, India: 605-609. https://doi.org/10.1109/ICSTCEE49637.2020.9277193   [Google Scholar]
  26. Sahoo MS and Baruah PK (2018). HbasechainDB–A scalable blockchain framework on hadoop ecosystem. In: Yokota R and Wu W (Eds.), Supercomputing Frontiers. SCFA 2018. Lecture Notes in Computer Science,Volume 10776. Springer, Cham, Switzerland. https://doi.org/10.1007/978-3-319-69953-0_2   [Google Scholar]
  27. Samad A. (2022). Internet of Things integrated with blockchain and artificial intelligence in healthcare system. Research Journal of Computer Systems and Engineering, 3(1): 1-6.   [Google Scholar]
  28. Sanjana T, Sowmya BJ, Kumar DP, and Srinivasa KG (2021). A framework for a secure e-health care system using IoT-based Blockchain technology. In: Sharma SK, Bhushan B, Khamparia A, Astya PN, and Debnath NC (Eds.), Blockchain technology for data privacy management: 253-273. CRC Press, Boca Raton, USA. https://doi.org/10.1201/9781003133391-12   [Google Scholar]
  29. Siyal AA, Junejo AZ, Zawish M, Ahmed K, Khalil A, and Soursou G (2019). Applications of blockchain technology in medicine and healthcare: Challenges and future perspectives. Cryptography, 3(1): 3. https://doi.org/10.3390/cryptography3010003   [Google Scholar]
  30. Tagde P, Tagde S, Bhattacharya T, Tagde P, Chopra H, Akter R, Kaushik D, and Rahman MH (2021). Blockchain and artificial intelligence technology in e-health. Environmental Science and Pollution Research, 28: 52810-52831. https://doi.org/10.1007/s11356-021-16223-0   [Google Scholar] PMid:34476701 PMCid:PMC8412875
  31. Veeramakali T, Siva R, Sivakumar B, Senthil Mahesh PC, and Krishnaraj N (2021). An intelligent Internet of Things-based secure healthcare framework using blockchain technology with an optimal deep learning model. The Journal of Supercomputing, 77(9): 9576-9596. https://doi.org/10.1007/s11227-021-03637-3   [Google Scholar]
  32. Velliyangiri G, Krishnamoorthy V, Inbaraj C, Venkatachalam A, Rahim R, and Ramachandran M (2022). Blockchain and artificial intelligent for Internet of Things in e-health. In: Goundar S, Suseendran G, and Anandan R (Eds.), The convergence of artificial intelligence and blockchain technologies: Challenges and opportunities: 23-42. World Scientific Publishing Company, Singapore, Singapore. https://doi.org/10.1142/9789811225079_0002   [Google Scholar]
  33. Verma G (2024). Blockchain-based privacy preservation framework for healthcare data in cloud environment. Journal of Experimental and Theoretical Artificial Intelligence, 36(1): 147-160. https://doi.org/10.1080/0952813X.2022.2135611   [Google Scholar]
  34. Wong ZS, Zhou J, and Zhang Q (2019). Artificial intelligence for infectious disease big data analytics. Infection, Disease and Health, 24(1): 44-48. https://doi.org/10.1016/j.idh.2018.10.002   [Google Scholar] PMid:30541697