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BlockFaaS: Blockchain-enabled Serverless Computing Framework for AI-driven IoT Healthcare Applications

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Abstract

With the development of new sensor technologies, Internet of Things (IoT)-based healthcare applications have gained momentum in recent years. However, IoT devices have limited resources, making them incapable of executing large computational operations. To solve this problem, the serverless paradigm, with its advantages such as dynamic scalability and infrastructure management, can be used to support the requirements of IoT-based applications. However, due to the heterogeneous structure of IoT, user trust must also be taken into account when providing this integration. This problem can be overcome by using a Blockchain that guarantees data immutability and ensures that any data generated by the IoT device is not modified. This paper proposes a BlockFaaS framework that supports dynamic scalability and guarantees security and privacy by integrating a serverless platform and Blockchain architecture into latency-sensitive Artificial Intelligence (AI)-based healthcare applications. To do this, we deployed the AIBLOCK framework, which guarantees data immutability in smart healthcare applications, into HealthFaaS, a serverless-based framework for heart disease risk detection. To expand this framework, we used high-performance AI models and a more efficient Blockchain module. We use the Transport Layer Security (TLS) protocol in all communication channels to ensure privacy within the framework. To validate the proposed framework, we compare its performance with the HealthFaaS and AIBLOCK frameworks. The results show that BlockFaaS outperforms HealthFaaS with an AUC of 4.79% and consumes 162.82 millijoules less energy on the Blockchain module than AIBLOCK. Additionally, the cold start latency value occurring in Google Cloud Platform, the serverless platform into which BlockFaaS is integrated, and the factors affecting this value are examined.

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References

  1. Das, S.K., Benkhelifa, F., Sun, Y., Abumarshoud, H., Abbasi, Q.H., Imran, M.A., Mohjazi, L.: Comprehensive review on ml-based ris-enhanced iot systems: basics, research progress and future challenges. Comput. Netw., 109581 (2023)

  2. Dian, F.J., Vahidnia, R., Rahmati, A.: Wearables and the internet of things (iot), applications, opportunities, and challenges: a survey. IEEE access 8, 69200–69211 (2020)

    Article  Google Scholar 

  3. Shanthamallu, U.S., Spanias, A., Tepedelenlioglu, C., Stanley, M.: A brief survey of machine learning methods and their sensor and iot applications. In: 2017 8th International conference on information, intelligence, systems & applications (IISA). IEEE, pp. 1–8 (2017)

  4. Kumar, M., et al.: Blockchain inspired secure and reliable data exchange architecture for cyber-physical healthcare system 4.0. Internet of Things and Cyber-Physical Systems 3, 309–322 (2023)

    Article  Google Scholar 

  5. Gill, S.S., Tuli, S., Xu, M., Singh, I., Singh, K.V., Lindsay, D., Tuli, S., Smirnova, D., Singh, M., Jain, U., et al.: Transformative effects of iot, blockchain and artificial intelligence on cloud computing: evolution, vision, trends and open challenges. Internet of Things 8, 100118 (2019)

    Article  Google Scholar 

  6. Golec, M., Ozturac, R., Pooranian, Z., Gill, S.S., Buyya, R.: Ifaasbus: a security-and privacy-based lightweight framework for serverless computing using iot and machine learning. IEEE Transactions on Industrial Informatics 18(5), 3522–3529 (2021)

    Article  Google Scholar 

  7. Golec, M., Chowdhury, D., Jaglan, S., Gill, S.S., Uhlig, S.: Aiblock: blockchain based lightweight framework for serverless computing using ai. In: 2022 22nd IEEE international symposium on cluster, cloud and internet computing (CCGrid). IEEE, pp. 886–892 (2022)

  8. Golec, M., Gill, S.S., Parlikad, A.K., Uhlig, S.: Healthfaas: ai based smart healthcare system for heart patients using serverless computing. IEEE Internet of Things Journal (2023)

  9. Madden, N.: Misuse-resistant cryptography for jose/jwt. Position paper (2018)

  10. Kubovy, J., Huber, C., Jäger, M., Küng, J.: A secure token-based communication for authentication and authorization servers. In: Future data and security engineering: third international conference, FDSE 2016, Can Tho City, Vietnam, November 23–25, 2016, Proceedings 3. Springer, pp. 237–250 (2016)

  11. Zahoor, S., Mir, R.N.: Resource management in pervasive internet of things: a survey. Journal of King Saud University-Computer and Information Sciences 33(8), 921–935 (2021)

    Article  Google Scholar 

  12. Samriya, J.K., et al.: Secured data offloading using reinforcement learning and markov decision process in mobile edge computing. Int. J. Netw. Manag., 2243 (2023)

  13. Liu, B., Yu, X.L., Chen, S., Xu, X., Zhu, L.: Blockchain based data integrity service framework for iot data. In: 2017 IEEE International conference on web services (ICWS). IEEE, pp. 468–475 (2017)

  14. Kumar, R., et al.: A robust and secure user authentication scheme based on multifactor and multi-gateway in iot enabled sensor networks. Secur. Priv., 335 (2023)

  15. Liu, Y., Yu, J., Fan, J., Vijayakumar, P., Chang, V.: Achieving privacy-preserving dsse for intelligent iot healthcare system. IEEE Transactions on Industrial Informatics 18(3), 2010–2020 (2021)

    Article  Google Scholar 

  16. Zhang, R., Xue, R., Liu, L.: Security and privacy on blockchain. ACM Comput. Surv. (CSUR) 52(3), 1–34 (2019)

    Article  Google Scholar 

  17. Singh, S., Chana, I., Singh, M.: The journey of qos-aware autonomic cloud computing. IT Prof. 19(2), 42–49 (2017)

    Article  Google Scholar 

  18. Singh, S., Chana, I.: A survey on resource scheduling in cloud computing: issues and challenges. Journal of grid computing 14, 217–264 (2016)

    Article  Google Scholar 

  19. Gill, S.S., Xu, M., Ottaviani, C., Patros, P., Bahsoon, R., Shaghaghi, A., Golec, M., Stankovski, V., Wu, H., Abraham, A., et al.: Ai for next generation computing: Emerging trends and future directions. Internet of Things 19, 100514 (2022)

    Article  Google Scholar 

  20. Apostolopoulos, P.A., Tsiropoulou, E.E., Papavassiliou, S.: Risk-aware social cloud computing based on serverless computing model. In: 2019 IEEE Global communications conference (GLOBECOM). IEEE, pp. 1–6 (2019)

  21. Cicconetti, C., Conti, M., Passarella, A., Sabella, D.: Toward distributed computing environments with serverless solutions in edge systems. IEEE Commun. Mag. 58(3), 40–46 (2020)

    Article  Google Scholar 

  22. Suo, H., Wan, J., Zou, C., Liu, J.: Security in the internet of things: a review. In: 2012 International conference on computer science and electronics engineering, vol. 3. IEEE, pp. 648–651 (2012)

  23. Iftikhar, S., et al.: Ai-based fog and edge computing: a systematic review, taxonomy and future directions. Internet of Things 21, 100674 (2022)

    Article  Google Scholar 

  24. Samonas, S., Coss, D.: The cia strikes back: redefining confidentiality, integrity and availability in security. Journal of Information System Security 10(3) (2014)

  25. Yeboah-Boateng, E.O.: Cyber-security challenges with smes in developing economies: issues of Confidentiality, Integrity & Availability (CIA). Institut for Elektroniske Systemer, Aalborg Universitet, ??? (2013)

  26. Kelly, G., McKenzie, B., et al.: Security, privacy, and confidentiality issues on the internet. Journal of Medical Internet Research 4(2), 861 (2002)

    Article  Google Scholar 

  27. Waheed, N., He, X., Ikram, M., Usman, M., Hashmi, S.S., Usman, M.: Security and privacy in iot using machine learning and blockchain: threats and countermeasures. ACM Comput. Surv. (CSUR) 53(6), 1–37 (2020)

    Article  Google Scholar 

  28. Ning, J., Huang, X., Poh, G.S., Xu, S., Loh, J.-C., Weng, J., Deng, R.H.: Pine: enabling privacy-preserving deep packet inspection on tls with rule-hiding and fast connection establishment. In: Computer security–ESORICS 2020: 25th European symposium on research in computer security, ESORICS 2020, Guildford, UK, September 14–18, 2020, Proceedings, Part I 25. Springer, pp. 3–22 (2020)

  29. Zikratov, I., Kuzmin, A., Akimenko, V., Niculichev, V., Yalansky, L.: Ensuring data integrity using blockchain technology. In: 2017 20th Conference of open innovations association (FRUCT). IEEE, pp. 534–539 (2017)

  30. Aminzade, M.: Confidentiality, integrity and availability-finding a balanced it framework. Netw. Secur. 2018(5), 9–11 (2018)

    Article  Google Scholar 

  31. Kumar, P.R., Raj, P.H., Jelciana, P.: Exploring data security issues and solutions in cloud computing. Procedia Computer Science 125, 691–697 (2018)

    Article  Google Scholar 

  32. Ye, T., Luo, M., Yang, Y., Choo, K.-K.R., He, D.: A survey on redactable blockchain: challenges and opportunities. IEEE Transactions on Network Science and Engineering (2023)

  33. Zheng, Z., Xie, S., Dai, H.-N., Chen, X., Wang, H.: Blockchain challenges and opportunities: a survey. International journal of web and grid services 14(4), 352–375 (2018)

    Article  Google Scholar 

  34. Singh, R., et al.: Edge ai: a survey. Internet of Things and Cyber-Physical Systems 3, 71–92 (2023)

    Article  Google Scholar 

  35. Al-Shareeda, M.A., Anbar, M., Manickam, S., Hasbullah, I.H.: Review of prevention schemes for man-in-the-middle (mitm) attack in vehicular ad hoc networks. International Journal of Engineering and Management Research 10 (2020)

  36. Ahmad, U., Song, H., Bilal, A., Saleem, S., Ullah, A.: Securing insulin pump system using deep learning and gesture recognition. In: 2018 17th IEEE International conference on trust, security and privacy in computing and communications/12th IEEE International conference on big data science and engineering (TrustCom/BigDataSE). IEEE, pp. 1716–1719 (2018)

  37. Turner, S.: Transport layer security. IEEE Internet Computing 18(6), 60–63 (2014)

    Article  MathSciNet  Google Scholar 

  38. Chan, C.-l., Fontugne, R., Cho, K., Goto, S.: Monitoring tls adoption using backbone and edge traffic. In: IEEE INFOCOM 2018-IEEE conference on computer communications corkshops (INFOCOM WKSHPS). IEEE, pp. 208–213 (2018)

  39. Golec, M., Gill, S.S., Bahsoon, R., Rana, O.: Biosec: a biometric authentication framework for secure and private communication among edge devices in iot and industry 4.0. IEEE Consumer Electronics Magazine 11(2), 51–56 (2020)

    Article  Google Scholar 

  40. Bıçakcı, H.S., Santopietro, M., Boakes, M., Guest, R.: Evaluation of electrocardiogram biometric verification models based on short enrollment time on medical and wearable recorders. In: 2021 International carnahan conference on security technology (ICCST). IEEE, pp. 1–6 (2021)

  41. Taloba, A.I., Elhadad, A., Rayan, A., Abd El-Aziz, R.M., Salem, M., Alzahrani, A.A., Alharithi, F.S., Park, C.: A blockchain-based hybrid platform for multimedia data processing in iot-healthcare. Alexandria Engineering Journal 65, 263–274 (2023)

    Article  Google Scholar 

  42. Sharma, P., Namasudra, S., Crespo, R.G., Parra-Fuente, J., Trivedi, M.C.: Ehdhe: enhancing security of healthcare documents in iot-enabled digital healthcare ecosystems using blockchain. Inf. Sci. 629, 703–718 (2023)

  43. Gupta, P., Chouhan, A.V., Wajeed, M.A., Tiwari, S., Bist, A.S., Puri, S.C.: Prediction of health monitoring with deep learning using edge computing. Measurement: Sensors 25, 100604 (2023)

  44. Balasundaram, A., Routray, S., Prabu, A., Krishnan, P., Malla, P.P., Maiti, M.: Internet of things (iot) based smart healthcare system for efficient diagnostics of health parameters of patients in emergency care. IEEE Internet of Things Journal (2023)

  45. Doyle, J., Golec, M., Gill, S.S.: Blockchainbus: a lightweight framework for secure virtual machine migration in cloud federations using blockchain. Secur. Priv. 5(2), 197 (2022)

    Article  Google Scholar 

  46. Benedict, S.: Serverless blockchain-enabled architecture for iot societal applications. IEEE Transactions on Computational Social Systems 7(5), 1146–1158 (2020). https://doi.org/10.1109/TCSS.2020.3008995

    Article  Google Scholar 

  47. Ayub Khan, A., Wagan, A.A., Laghari, A.A., Gilal, A.R., Aziz, I.A., Talpur, B.A.: Biomt: a state-of-the-art consortium serverless network architecture for healthcare system using blockchain smart contracts. IEEE Access 10, 78887–78898 (2022). https://doi.org/10.1109/ACCESS.2022.3194195

    Article  Google Scholar 

  48. Winderickx, J., Braeken, A., Singelee, D., Mentens, N.: In-depth energy analysis of security algorithms and protocols for the internet of things. Journal of Cryptographic Engineering 12(2), 137–149 (2022)

    Article  Google Scholar 

  49. Fan, Y., Winkel, C., Kulkarni, D., Tian, W.: Analytical design methodology for liquid based cooling solution for high tdp cpus. In: 2018 17th IEEE Intersociety conference on thermal and thermomechanical phenomena in electronic systems (ITherm). IEEE, pp. 582–586 (2018)

  50. Dworkin, M.J.: Sha-3 standard: permutation-based hash and extendable-output functions (2015)

  51. Gligoroski, D.: Length extension attack on narrow-pipe sha-3 candidates. In: International conference on ICT innovations. Springer, pp. 5–10 (2010)

  52. https://archive.ics.uci.edu/ml/datasets/Heart+Disease,lastaccessedon=2023-04-30 (2023). Accessed 30 April 2023

  53. Google. https://cloud.google.com/functions (2023)

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Acknowledgements

Muhammed Golec would express his thanks to the Ministry of Education of the Turkish Republic for their support and funding. This work is partially funded by Chinese Academy of Sciences President’s International Fellowship Initiative (Grant No. 2023VTC0006). The authors would like to thank the Editor-in-Chief, area editor and anonymous reviewers for their valuable comments and helpful suggestions to improve the quality of the paper.

Funding

This work is partially funded by Chinese Academy of Sciences President’s International Fellowship Initiative (Grant No. 2023VTC0006)

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Authors and Affiliations

  1. School of Electronic Engineering and Computer Science, Queen Mary University of London, United Kingdom and Abdullah Gul University, Kayseri, Turkey

    Muhammed Golec

  2. School of Electronic Engineering and Computer Science, Queen Mary University of London, London, United Kingdom

    Sukhpal Singh Gill & Steve Uhlig

  3. Kütahya Dumlupınar University, Kütahya, Turkey

    Mustafa Golec

  4. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Minxian Xu

  5. Department of Computer Science and Engineering, Indian Institute of Technology, Kharagpur, India

    Soumya K. Ghosh

  6. School of Computer Science and Engineering, The University of New South Wales (UNSW), Sydney, Australia

    Salil S. Kanhere

  7. School of Computer Science and Informatics, Cardiff University, Cardiff, UK

    Omer Rana

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  1. Muhammed Golec
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Contributions

Muhammed Golec (Conceptualization: Lead; Data curation: Lead; Formal analysis: Lead; Funding acquisition: Lead; Investigation: Lead; Methodology: Lead; Software: Lead; Validation: Lead; Writing - original draft: Lead) Sukhpal Singh Gill (Conceptualization: Lead; Data curation: Lead; Formal analysis: Lead; Funding acquisition: Lead; Investigation: Lead; Methodology: Lead; Software: Lead; Validation: Lead; Writing - original draft: Lead) Mustafa Golec (Conceptualization: Lead; Data curation: Lead; Formal analysis: Lead; Investigation: Lead; Methodology: Lead; Software: Lead; Validation: Lead; Writing - original draft: Lead) Minxian Xu (Conceptualization: Lead; Formal analysis: Lead; Funding acquisition: Lead; Investigation: Lead; Methodology: Lead; Writing - original draft: Lead) Soumya K. Ghosh (Supervision: Supporting; ; Writing - original draft: Lead; Writing - review & editing: Supporting) Salil S. Kanhere (Supervision: Supporting; ; Writing - original draft: Lead; Writing - review & editing: Supporting) Omer Rana (Supervision: Supporting; ; Writing - original draft: Lead; Writing - review & editing: Supporting) Steve Uhlig (Supervision: Supporting; ; Writing - original draft: Lead; Writing - review & editing: Supporting)

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Correspondence to Muhammed Golec.

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Golec, M., Gill, S.S., Golec, M. et al. BlockFaaS: Blockchain-enabled Serverless Computing Framework for AI-driven IoT Healthcare Applications. J Grid Computing 21, 63 (2023). https://doi.org/10.1007/s10723-023-09691-w

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