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Emergence of Healthcare 4.0 and Blockchain into Secure Cloud-based Electronic Health Records Systems: Solutions, Challenges, and Future Roadmap

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Abstract

Since the last decade, cloud-based Electronic Health Records (EHRs) have achieved important consideration to facilitate remote access of patient medical records. The modern evolution of Healthcare 4.0 applying the Internet of Things (IoT) elements with cloud computing reforms to obtain remote medical services has grown the researcher’s recognition with the perspective of the smart city. The Healthcare 4.0 standard has consists of different layers to perform medical operations like periodic data sensing, data storage, data sharing, and auditing. The delicate and private medical records of victims lead to numerous difficulties while defending them from hackers. Therefore saving, obtaining, and distributing the patient medical data on the remote storage requires safety attentions so that medical records should not be compromised by the authorized user’s components of E-healthcare systems. To achieve secure medical data storage, sharing, and accessing in Cloud Service Provider (CSP), various cryptography algorithms have been designed so far. But these traditional resolutions disappointed to manage the trade-off among the provisions of EHR safety in terms of computational competence, user-side verification, service-side verification, security, and without the trusted third party. Blockchain-based security techniques achieved notable recognition due to the strength to give strong security provisions for medical records storage and sharing with the least computation forces. The blockchain made focused on bitcoin technology among the researchers. Employing the blockchain in healthcare systems has been of current interest. This paper aims to present a systematic study of different blockchain-based solutions for the smart healthcare 4.0 system. The recent blockchain-based security solutions have been reviewed first and, then we presented a research gap considering the various parameters. The outcome of this paper discusses the current research gaps, the challenges of implementing the blockchain-based secure healthcare system, and the future roadmap or solutions.

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References

  1. Taichman, D. B., Backus, J., Baethge, C., Bauchner, H., de Leeuw, P. W., Drazen, J. M. … Wu, S. N. (2016). Sharing Clinical Trial Data. Chinese Medical Journal, 129(2), 127–128. https://doi.org/10.4103/0366-6999.173420.

    Article  Google Scholar 

  2. Chen, M., Mao, S., & Liu, Y. (2014). Big Data: A Survey. Mobile Networks and Applications, 19(2), 171–209. https://doi.org/10.1007/s11036-013-0489-0.

    Article  Google Scholar 

  3. Mikhail, A., Kamil, I. A., & Mahajan, H. (2017). Increasing SCADA System Availability by Fault Tolerance Techniques. 2017 International Conference on Computing, Communication, Control and Automation (ICCUBEA). https://doi.org/10.1109/iccubea.2017.8463911

  4. Krumholz, H. M., & Waldstreicher, J. (2016). The Yale Open Data Access (YODA) Project — A Mechanism for Data Sharing. New England Journal of Medicine, 375(5),403–405. https://doi.org/10.1056/nejmp1607342.

  5. Mikhail, A., Kareem, H. H., & Mahajan, H. (2017). Fault Tolerance to Balance for Messaging Layers in Communication Society. 2017 International Conference on Computing, Communication, Control and Automation (ICCUBEA). https://doi.org/10.1109/iccubea.2017.8463871

  6. Huang, J., Fang, F., Sun, Y., Yan, H., Xing, C., Duan, Q., & Wang, W. (2014). A New Economic Model in Cloud Computing: Cloud Service Provider vs. Network Service Provider. 2015 IEEE Global Communications Conference (GLOBECOM). https://doi.org/10.1109/glocom.2014.7417298

  7. Huang, J., Duan, Q., Guo, S., Yan, Y., & Yu, S. (2018). Converged Network-Cloud Service Composition with End-to-End Performance Guarantee. IEEE Transactions on Cloud Computing, 6(2), 545–557. https://doi.org/10.1109/tcc.2015.2491939.

    Article  Google Scholar 

  8. Aceto, G., Botta, A., de Donato, W., & Pescapè, A. (2013). Cloud monitoring: A survey. Computer Networks, 57(9), 2093–2115. https://doi.org/10.1016/j.comnet.2013.04.001.

    Article  Google Scholar 

  9. Assis, M. R. M., Bittencourt, L. F., & Tolosana-Calasanz, R. (2014). Cloud Federation: Characterisation and Conceptual Model. 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing. https://doi.org/10.1109/ucc.2014.90

  10. O’Driscoll, A., Daugelaite, J., & Sleator, R. D. (2013).). “Big data”, Hadoop and cloud computing in genomics. Journal of Biomedical Informatics, 46(5), 774–781. https://doi.org/10.1016/j.jbi.2013.07.001.

    Article  MATH  Google Scholar 

  11. Borgman, C. L. (2011). The Conundrum of Sharing Research Data. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.1869155.

    Article  Google Scholar 

  12. Grozev, N., & Buyya, R. (2012). Inter-Cloud architectures and application brokering: taxonomy and survey. Software: Practice and Experience, 44(3), 369–390. https://doi.org/10.1002/spe.2168.

    Article  Google Scholar 

  13. Fazio, M., Celesti, A., Villari, M., & Puliafito, A. (2015). How to Enhance Cloud Architectures to Enable Cross-Federation: Towards Interoperable Storage Providers. 2015 IEEE International Conference on Cloud Engineering. https://doi.org/10.1109/ic2e.2015.80

  14. Kuo, M. H. (2011). Opportunities and Challenges of Cloud Computing to Improve Health Care Services. Journal of medical Internet research, 13, e67. https://doi.org/10.2196/jmir.1867

    Article  Google Scholar 

  15. Weber, G. M., Mandl, K. D., & Kohane, I. S. (2014). Finding the Missing Link for Big Biomedical Data. JAMA. https://doi.org/10.1001/jama.2014.4228

    Article  Google Scholar 

  16. Shao, J., Lu, R., & Lin, X. (2015). Fine-grained data sharing in cloud computing for mobile devices. 2015 IEEE Conference on Computer Communications (INFOCOM). https://doi.org/10.1109/infocom.2015.7218659

  17. Thilakanathan, D., Chen, S., Nepal, S., Calvo, R. A., Liu, D., & Zic, J. (2014). Secure Multiparty Data Sharing in the Cloud Using Hardware-Based TPM Devices. 2014 IEEE 7th International Conference on Cloud Computing. https://doi.org/10.1109/cloud.2014.39

  18. Khan, A. N., Kiah, M. L. M., Ali, M., Madani, S. A., Khan, A., & Shamshirband, S. (2014). BSS: block-based sharing scheme for secure data storage services in mobile cloud environment. The Journal of Supercomputing, 70(2), 946–976. https://doi.org/10.1007/s11227-014-1269-8.

    Article  Google Scholar 

  19. Dong, X., Yu, J., Luo, Y., Chen, Y., Xue, G., & Li, M. (2014). Achieving an effective, scalable and privacy-preserving data sharing service in cloud computing. Computers & Security, 42, 151–164. https://doi.org/10.1016/j.cose.2013.12.002

    Article  Google Scholar 

  20. Yang, J. J., Li, J. Q., & Niu, Y. (2015). A hybrid solution for privacy preserving medical data sharing in the cloud environment. Future Generation Computer Systems, 43–44, 74–86. https://doi.org/10.1016/j.future.2014.06.004

    Article  Google Scholar 

  21. Tschorsch, F., & Scheuermann, B. (2016). Bitcoin and Beyond: A Technical Survey on Decentralized Digital Currencies. IEEE Communications Surveys & Tutorials, 18(3), 2084–2123. https://doi.org/10.1109/comst.2016.2535718

    Article  Google Scholar 

  22. Azaria, A., Ekblaw, A., Vieira, T., Lippman, A., & Permission Management. (2016). MedRec: Using Blockchain for Medical Data Access and. 2016 2nd International Conference on Open and Big Data (OBD). https://doi.org/10.1109/obd.2016.11

  23. Zhang, J., Xue, N., & Huang, X. (2016). A Secure System For Pervasive Social Network-Based Healthcare. IEEE Access, 4, 9239–9250. https://doi.org/10.1109/access.2016.2645904.

    Article  Google Scholar 

  24. Nepal, S., Ranjan, R., & Choo, K. K. R. (2015). Trustworthy Processing of Healthcare Big Data in Hybrid Clouds. IEEE Cloud Computing, 2(2),78–84. https://doi.org/10.1109/mcc.2015.36.

  25. Poh, G. S., Chin, J. J., Yau, W. C., Choo, K. K. R., & Mohamad, M. S. (2017). Searchable Symmetric Encryption. ACM Computing Surveys, 50(3), 1–37. https://doi.org/10.1145/3064005

    Article  Google Scholar 

  26. Alam, Q., Malik, S. U. R., Akhunzada, A., Choo, K. K. R., Tabbasum, S., & Alam, M. (2017). A Cross Tenant Access Control (CTAC) Model for Cloud Computing: Formal Specification and Verification. IEEE Transactions on Information Forensics and Security, 12(6), 1259–1268. https://doi.org/10.1109/tifs.2016.2646639

    Article  Google Scholar 

  27. Li, M., Yu, S., Zheng, Y., Ren, K., & Lou, W. (2013). Scalable and Secure Sharing of Personal Health Records in Cloud Computing Using Attribute-Based Encryption. Parallel and Distributed Systems. IEEE Transactions on, 24, 131–143. https://doi.org/10.1109/TPDS.2012.97.

    Article  Google Scholar 

  28. Xu, J. J. (2016). Are blockchains immune to all malicious attacks? Financial Innovation, 2(1). https://doi.org/10.1186/s40854-016-0046-5.

  29. Niranjanamurthy, M., Nithya, B. N., & Jagannatha, S. (2018). Analysis of Blockchain technology: pros, cons and SWOT. Cluster Computing. https://doi.org/10.1007/s10586-018-2387-5

    Article  Google Scholar 

  30. Dinh, T. T. A., Liu, R., Zhang, M., Chen, G., Ooi, B. C., & Wang, J. (2018). Untangling Blockchain: A Data Processing View of Blockchain Systems. IEEE Transactions on Knowledge and Data Engineering, 30(7), 1366–1385. https://doi.org/10.1109/tkde.2017.2781227.

  31. Ocheja, P., Flanagan, B., Ueda, H., & Ogata, H. (2019). Managing lifelong learning records through blockchain. Research and Practice in Technology Enhanced Learning, 14(1). https://doi.org/10.1186/s41039-019-0097-0

  32. Shahzad, B., & Crowcroft, J. (2019). Fast Iterative Semi-Blind Receiver for URLLC in Short-Frame Full-Duplex Systems with CFO. IEEE Access, 1–1. https://doi.org/10.1109/access.2019.2895670

  33. Turkanovic, M., Holbl, M., Kosic, K., Hericko, M., & Kamisalic, A. (2018). EduCTX: A Blockchain-Based Higher Education Credit Platform. IEEE Access, 6, 5112–5127. https://doi.org/10.1109/access.2018.2789929

    Article  Google Scholar 

  34. Kshetri, N., & Voas, J. (2018). Blockchain-Enabled E-Voting. IEEE Software, 35(4), 95–99. https://doi.org/10.1109/ms.2018.2801546

    Article  Google Scholar 

  35. Chen, G., Xu, B., Lu, M., & Chen, N. S. (2018). Exploring blockchain technology and its potential applications for education. Smart Learning Environments, 5(1). https://doi.org/10.1186/s40561-017-0050-x

  36. Bistarelli, S., Mercanti, I., Santancini, P., & Santini, F. (2019). End-to-End Voting with Non-Permissioned and Permissioned Ledgers. Journal of Grid Computing. https://doi.org/10.1007/s10723-019-09478-y

    Article  Google Scholar 

  37. Knirsch, F., Unterweger, A., & Engel, D. (2019). Implementing a blockchain from scratch: why, how, and what we learned. EURASIP Journal on Information Security, 2019(1). https://doi.org/10.1186/s13635-019-0085-3

  38. Pirtle, C., & Ehrenfeld, J. (2018). Blockchain for Healthcare: The Next Generation of Medical Records? Journal of Medical Systems, 42(9). https://doi.org/10.1007/s10916-018-1025-3

  39. Scriber, B. (2018). A Framework for Determining Blockchain Applicability. IEEE Software, 35, 70–77. https://doi.org/10.1109/MS.2018.2801552.

    Article  Google Scholar 

  40. Esposito, C., De Santis, A., Tortora, G., Chang, H., & Choo, K. K. R. (2018). Blockchain: A Panacea for Healthcare Cloud-Based Data Security and Privacy? IEEE Cloud Computing, 5(1),31–37. https://doi.org/10.1109/mcc.2018.011791712

  41. Kshetri, N. (2018). Blockchain and Electronic HealthcareRecords [Cybertrust]. Computer, 51(12),59–63. https://doi.org/10.1109/mc.2018.2880021

  42. Chen, L., Lee, W. K., Chang, C. C., Choo, K. K. R., & Zhang, N. (2019). Blockchain based searchable encryption for electronic health record sharing. Future Generation Computer Systems. https://doi.org/10.1016/j.future.2019.01.018

    Article  Google Scholar 

  43. Wang, S., Wang, J., Wang, X., Qiu, T., Yuan, Y., Ouyang, L., … Wang, F.-Y. (2018).Blockchain-Powered Parallel Healthcare Systems Based on the ACP Approach. IEEE Transactions on Computational Social Systems, 1–9. https://doi.org/10.1109/tcss.2018.2865526

  44. Zhao, H., Bai, P., Peng, Y., & Xu, R. (2018). Efficient key management scheme for health blockchain. CAAI Transactions on Intelligence Technology, 3(2), 114–118. https://doi.org/10.1049/trit.2018.0014

    Article  Google Scholar 

  45. Zhang, P., White, J., Schmidt, D. C., Lenz, G., & Rosenbloom, S. T. (2018). FHIRChain: Applying Blockchain to Securely and Scalably Share Clinical Data. Computational and Structural Biotechnology Journal, 16,267–278. https://doi.org/10.1016/j.csbj.2018.07.004.

  46. Kamel Boulos, M. N., Wilson, J. T., & Clauson, K. A. (2018). Geospatial blockchain: promises, challenges, and scenarios in health and healthcare. International Journal of Health Geographics, 17(1). https://doi.org/10.1186/s12942-018-0144-x

  47. Zhou, L., Wang, L., & Sun, Y. (2018). MIStore: a Blockchain-Based Medical Insurance Storage System. Journal of Medical Systems, 42(8). https://doi.org/10.1007/s10916-018-0996-4.

  48. Xia, Q., Sifah, E., Smahi, A., Amofa, S., & Zhang, X. (2017). BBDS: Blockchain-Based Data Sharing for Electronic Medical Recordsin Cloud Environments. Information, 8(2),44. https://doi.org/10.3390/info8020044

  49. Xia, Q., Sifah, E. B., Asamoah, K. O., Gao, J., Du, X., & Guizani, M. (2017). MeDShare: Trust-Less Medical Data Sharing Among Cloud Service Providers via Blockchain. IEEE Access, 5, 14757–14767. https://doi.org/10.1109/access.2017.2730843

  50. Gao, Y., Chen, X., Sun, Y., Niu, Xinxin, & Yang Yixian. (2018). A Secure Cryptocurrency Scheme based on Post-Quantum Blockchain. IEEE Access. PP. 1–1. https://doi.org/10.1109/ACCESS.2018.2827203

  51. Zhang, Y., Deng, R. H., Shu, J., Yang, K., & Zheng, D. (2018). TKSE: Trustworthy Keyword Search Over Encrypted Data With Two-Side Verifiability via Blockchain. IEEE Access, 6, 31077–31087. https://doi.org/10.1109/access.2018.2844400.

  52. Chen, Y., Ding, S., Xu, Z., Zheng, H., & Yang, S. (2018). Blockchain-Based Medical Records Secure Storage and Medical Service Framework. Journal of Medical Systems, 43(1). https://doi.org/10.1007/s10916-018-1121-4

  53. Thwin, T. T., & Vasupongayya, S. (2019). Blockchain-Based Access Control Model to Preserve Privacy for Personal Health Record Systems. Security and Communication Networks, 2019, 1–15

  54. Pournaghi, S. M., Bayat, M., & Farjami, Y. (2020). MedSBA: a novel and secure scheme to share medical data based on blockchain technology and attribute-based encryption. Journal of Ambient Intelligence and Humanized Computing. https://doi.org/10.1007/s12652-020-01710-y

    Article  Google Scholar 

  55. Rathee, G., Sharma, A., Saini, H., Kumar, R., & Iqbal, R. (2020). A hybrid framework for multimedia data processing in IoT-healthcare using blockchain technology. Multimedia Tools and Applications, 79. https://doi.org/10.1007/s11042-019-07835-3

  56. Rocha, Á., Adeli, H., Reis, L. P., Costanzo, S., Orovic, I., & Moreira, F. (Eds.). (2020). Trends and Innovations in Information Systems and Technologies. Advances in Intelligent Systems and Computing. https://doi.org/10.1007/978-3-030-45688-7

  57. Jmaiel, M., Mokhtari, M., Abdulrazak, B., Aloulou, H., & Kallel, S. (Eds.). (2020). The Impact of Digital Technologies on Public Health in Developed and Developing Countries. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-030-51517-1

  58. Shen, B., Guo, J., & Yang, Y. (2019). MedChain: Efficient Healthcare Data Sharing via Blockchain. Applied Sciences, 9(6),1207. https://doi.org/10.3390/app9061207

  59. Yang, G., Li, C., Kjell, E., & Marstein (2019). A blockchain-based architecture for securing electronic health record systems. Concurrency Computat Pract Exper. 2019; e5479

  60. Liu, X., Wang, Z., Jin, C., Li, F., & Li, G. (2019). A Blockchain-Based Medical Data Sharing and Protection Scheme. IEEE Access, 7,118943–118953. https://doi.org/10.1109/access.2019.2937685

  61. Uke, N., Pise, P., & Mahajan, H. B. et al., (2021). Healthcare 4.0 Enabled Lightweight Security Provisions for Medical Data Processing. Turkish Journal of Computer and Mathematics, (2021), 12(11). https://doi.org/10.17762/turcomat.v12i11.5858

  62. Mahajan, H. B., Badarla, A., & Junnarkar, A. A. (2021). CL-IoT: cross-layer Internet of Things protocol for intelligent manufacturing of smart farming. J Ambient Intell Human Comput, 12, 7777–7791. https://doi.org/10.1007/s12652-020-02502-0

    Article  Google Scholar 

  63. Mahajan, H. B., & Badarla, A. (2018). Application of Internet of Things for Smart Precision Farming: Solutions and Challenges. International Journal of Advanced Science and Technology, Dec. 2018, 37–45

  64. Mahajan, H. B., & Badarla, A. (2019). Experimental Analysis of Recent Clustering Algorithms for Wireless Sensor Network: Application of IoT based Smart Precision Farming. Jour of Adv Research in Dynamical & Control Systems, 11(9), https://doi.org/10.5373/JARDCS/V11I9/20193162

  65. Mahajan, H. B., & Badarla, A. (2020). Detecting HTTP Vulnerabilities in IoT-based Precision Farming Connected with Cloud Environment using Artificial Intelligence. International Journal of Advanced Science and Technology, 29(3), 214–226

    Google Scholar 

  66. Mahajan, H. B., & Badarla, A. (2021). Cross-Layer Protocol for WSN-Assisted IoT Smart Farming Applications Using Nature Inspired Algorithm. Wireless Pers Commun. https://doi.org/10.1007/s11277-021-08866-6

    Article  Google Scholar 

  67. Alhayani, B., Abbas, S. T., Mohammed, H. J., & Mahajan, H. B. (2021). Intelligent Secured Two-Way Image Transmission Using Corvus Corone Module over WSN. Wireless Pers Commun. https://doi.org/10.1007/s11277-021-08484-2

    Article  Google Scholar 

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    Hemant B. Mahajan

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Mahajan, H.B. Emergence of Healthcare 4.0 and Blockchain into Secure Cloud-based Electronic Health Records Systems: Solutions, Challenges, and Future Roadmap. Wireless Pers Commun 126, 2425–2446 (2022). https://doi.org/10.1007/s11277-022-09535-y

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