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Integrating Blockchain with Fog and Edge Computing for Micropayment Systems

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Security Issues in Fog Computing from 5G to 6G

Part of the book series: Internet of Things ((ITTCC))

Abstract

Fog computing eliminates the need for a centralized cloud data center as it allows computation to be done by nodes closer to the edge. This helps in improving scalability, latency, and throughput compared to traditional cloud environment. Furthermore, with massive increase of IoT devices in the coming future, current solutions that consider centralized cloud computing may not be suitable. Blockchain has developed as a powerful technology enabling unlimited application and opportunities during the last decade. As both blockchain and fog computing technologies operate on a decentralized framework for operations, their integration can help in driving many technologies forward and provide tremendous advantage in terms of security and cost. Recently, micropayments are adopted into a large number of applications. However, individually processing micropayments will result in higher transaction fees where in some cases transaction fee can exceed the payment value. Due to this reason, traditional cryptocurrency blockchain like Bitcoins is inappropriate for micropayment transactions. As such, using fog computing for micropayment can improve the latency and scalability. On the other side, the increased speed and connection density offered by 5G technology will enable real-time processing of data as well as automated transaction processing between connected devices. The 5G technology will enable the smart devices to make micropayments by processing data more efficiently. This will have far-reaching impact on business financial management. The 6G networks will exhibit more heterogeneity than 5G enabling different types of devices to communicate in an efficient way. This will enhance the micropayment networks where different types of IoT devices will be able to connect and hence process payments and transactions in a more secure way. Integrating this intelligence with big data in blockchain and fog computing will change the traditional business models and support the creation of efficient and fast micropayment systems.

This chapter explains the benefits of integrating modern technologies (fog computing, blockchain, 6G, and IoT) to solve the problem of micropayment systems. This is achieved by utilizing the capabilities of each technology (e.g., edge computing, blockchain, evolution of 5G to 6G) to bring intelligence from centralized computing facilities to edge/fog devices allowing for more envisioned applications such as micropayment systems where reliable, cheap, high speed, secure, and reduced latency transaction processing can be achieved. The chapter also highlights the various relationships among these technologies and surveys the most relevant work in order to analyze how the use of these disruptive technologies could potentially improve the micropayment systems functionality. Furthermore, various forms of integration of these technologies and associated applications are discussed, and solutions/challenges are outlined. The chapter also briefly discusses a generic solution to the problem of micropayments by integrating fog computing capabilities, blockchain, and edge computing to provide a practical payment setup that allows customers to issue micropayments in a convenient, fast, and secure manner.

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References

  1. Reyna, A., Martín, C., Chen, J., Soler, E., & Díaz, M. (2018). On blockchain and its integration with IoT. Challenges and opportunities. Future Generation Computer Systems, 88(2018), 173–190. https://doi.org/10.1016/j.future.2018.05.046

    Article  Google Scholar 

  2. Bouachir, O., Aloqaily, M., Tesng, L., & Boukerche, A. (2020). Blockchain and fog computing for cyber-physical systems: Case of smart industry. arXiv, 53, 36.

    Google Scholar 

  3. Singh, P., Nayyar, A., Kaur, A., & Ghosh, U. (2020). Blockchain and fog based architecture for internet of everything in smart cities. Futur, 12(4), 1–12. https://doi.org/10.3390/FI12040061

    Article  Google Scholar 

  4. Jang, B., Guejong, S. H., Jeong, J., & Sangmin, J. Fog computing architecture based blockchain for industrial IoT. International Conference on Computational Science Cham, 11538, 593–606. https://doi.org/10.1007/978-3-030-22744-9

  5. Baniata, H., & Kertesz, A. (2020). A survey on blockchain-fog integration approaches. IEEE Access, 8, 102657–102668. https://doi.org/10.1109/ACCESS.2020.2999213

    Article  Google Scholar 

  6. Memon, R. A., Li, J. P., Ahmed, J., Nazeer, M. I., Ismail, M., & Ali, K. (2020). Cloud-based vs. blockchain-based IoT: A comparative survey and way forward. Frontiers of Information Technology and Electronic Engineering, 21(4), 563–586. https://doi.org/10.1631/FITEE.1800343

    Article  Google Scholar 

  7. Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. www.Bitcoin.Org. https://doi.org/10.1007/s10838-008-9062-0.

  8. Fan, Y., Wang, L., Wu, W., & Du, D. (2021). Cloud/edge computing resource allocation and pricing for mobile blockchain: An iterative greedy and search approach. IEEE Transactions on Computational Social Systems, 1–13. https://doi.org/10.1109/TCSS.2021.3049152

  9. Liang, X., Shetty, S., Tosh, D., Kamhoua, C., Kwiat, K., & Njilla, L. (2017). ProvChain: A blockchain-based data provenance architecture in cloud environment with enhanced privacy and availability. Proceeding – 2017 17th IEEE/ACM International Symposium on Cluster Cloud and Grid Computing (CCGRID) 2017, pp. 468–477. https://doi.org/10.1109/CCGRID.2017.8.

  10. Liang, X., Shetty, S. S., Tosh, D., Njilla, L., Kamhoua, C. A., & Kwiat, K. (2019). ProvChain: Blockchain-based cloud data provenance. Blockchain for Distributed Systems Security, 69, 67–94.

    Article  Google Scholar 

  11. Nawaz, A., et al. (2020). Edge computing to secure iot data ownership and trade with the ethereum blockchain. Sensors (Switzerland), 20(14), 1–17. https://doi.org/10.3390/s20143965

    Article  MathSciNet  Google Scholar 

  12. Li, J., Wu, J., & Chen, L. (2018). Block-secure: Blockchain based scheme for secure P2P cloud storage. Information Sciences (NY), 465, 219–231. https://doi.org/10.1016/j.ins.2018.06.071

    Article  Google Scholar 

  13. Juneja, A., & Marefat, M. (2018). Leveraging blockchain for retraining deep learning architecture in patient-specific arrhythmia classification. 2018 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI) 2018, 2018, 393–397. https://doi.org/10.1109/BHI.2018.8333451

    Article  Google Scholar 

  14. Shafagh, H., Burkhalter, L., Hithnawi, A., & Duquennoy, S. (2017). Towards blockchain-based auditable storage and sharing of iot data. CCSW 2017 – Proceedings of the 2017 Cloud Computing Security Workshop, co-located with CCS 2017, 2017, 45–50. https://doi.org/10.1145/3140649.3140656

    Article  Google Scholar 

  15. Yuan, Y., & Wang, F. Y. (2018). Blockchain and cryptocurrencies: Model, techniques, and applications. IEEE Transactions on Systems, Man and Cybernetics: Systems, 48(9), 1421–1428. https://doi.org/10.1109/TSMC.2018.2854904

    Article  Google Scholar 

  16. Wang, S., Ouyang, L., Yuan, Y., Ni, X., Han, X., & Wang, F. Y. (2019). Blockchain-enabled smart contracts: Architecture, applications, and future trends. IEEE Transactions on Systems, Man and Cybernetics: Systems, 49(11), 2266–2277. https://doi.org/10.1109/TSMC.2019.2895123

    Article  Google Scholar 

  17. Tian, Z., Li, M., Qiu, M., Sun, Y., & Su, S. (2019). Block-DEF: A secure digital evidence framework using blockchain. Information Sciences, 491, 151–165. https://doi.org/10.1016/j.ins.2019.04.011

    Article  Google Scholar 

  18. Huang, B., Liu, Z., Chen, J., Liu, A., Liu, Q., & He, Q. (2017). Behavior pattern clustering in blockchain networks. Multimedia Tools and Applications, 76(19), 20099–20110. https://doi.org/10.1007/s11042-017-4396-4

    Article  Google Scholar 

  19. Deep, G., Mohana, R., Nayyar, A., Sanjeevikumar, P., & Hossain, E. (2019). Authentication protocol for cloud databases using blockchain mechanism. Sensors (Switzerland), 19(20), 1–13. https://doi.org/10.3390/s19204444

    Article  Google Scholar 

  20. Puthal, D., & Mohanty, S. P. (2019). Proof of authentication: IoT-friendly Blockchains. IEEE Potentials, 38(1), 26–29. https://doi.org/10.1109/MPOT.2018.2850541

    Article  Google Scholar 

  21. George, G., & Sankaranarayanan, S. (2019). Light weight cryptographic solutions for fog based blockchain. 6th IEEE International Conference on Smart Structures and Systems (ICSSS) 2019. https://doi.org/10.1109/ICSSS.2019.8882870.

  22. Carbone, A., Davcev, D., Mitreski, K., Kocarev, L., & Stankovski, V. (2018). Blockchain based distributed cloud fog platform for IoT Supply Chain Management, 51–58. https://doi.org/10.15224/978-1-63248-144-3-37

  23. Wu, D., & Ansari, N. (2020). A cooperative computing strategy for blockchain-secured fog computing. IEEE Internet of Things Journal, 7(7), 6603–6609. https://doi.org/10.1109/JIOT.2020.2974231

    Article  Google Scholar 

  24. Rahmani, A. M., et al. (2018). Exploiting smart e-health gateways at the edge of healthcare internet-of-things: A fog computing approach. Future Generation Computer Systems, 78, 641–658. https://doi.org/10.1016/j.future.2017.02.014

    Article  Google Scholar 

  25. Tuli, S., Mahmud, R., Tuli, S., & Buyya, R. (2018). FogBus: A blockchain-based lightweight framework for edge and fog computing. [Online]. Available: http://arxiv.org/abs/1811.11978.

  26. Lundqvist, T., De Blanche, A., & Andersson, H. R. H. Thing-to-thing electricity micro payments using blockchain technology. GIoTS 2017 – Global. Internet Things Summit, Proceeding, 2017. https://doi.org/10.1109/GIOTS.2017.8016254.

  27. Robert, J., Kubler, S., & Ghatpande, S. (2020). Enhanced lightning network (off-chain)-based micropayment in IoT ecosystems. Future Generation Computer Systems, 112, 283–296. https://doi.org/10.1016/j.future.2020.05.033

    Article  Google Scholar 

  28. Xu, Q., Li, M., Huang, X., Xue, N., Zhang, J., & Sheng. A blockchain based micro payment system for smart devices. Signature, 256(4936), 115.

    Google Scholar 

  29. Pouraghily, A., & Wolf, T. (2019). A lightweight payment verification protocol for blockchain transactions on IoT devices. 2019 International Conference on Computing. Networking and Communications (ICNC), 2019, 617–623. https://doi.org/10.1109/ICCNC.2019.8685545

    Article  Google Scholar 

  30. Hao, Z., Ji, R., & Li, Q. (2018). FastPay: A secure fast payment method for edge-IoT platforms using blockchain. Proceeding – 2018 The Third ACM/IEEE Symposium on Edge Computing (SEC 2018), pp. 410–415. https://doi.org/10.1109/SEC.2018.00055.

  31. Heilman, E., AlShenibr, L., Baldimtsi, F., Scafuro, A., & Goldberg, S. (2017). TumbleBit: An untrusted bitcoin-compatible anonymous payment hub. https://doi.org/10.14722/ndss.2017.23086

  32. Poon, T., & Dryja, J. (2016). The Bitcoin Lightning Network: Scalable off-chain instant payments. https://doi.org/10.3758/BF03205969

  33. Green, M., & Miers, I. (2017). Bolt: Anonymous payment channels for decentralized currencies. Proceedings of the ACM Conference on Computer and Communications Security, 2017, 473–489. https://doi.org/10.1145/3133956.3134093

    Article  Google Scholar 

  34. Lee, S., & Kim, H. (2020). On the robustness of lightning network in bitcoin. Pervasive and Mobile Computing, 61, 101108. https://doi.org/10.1016/j.pmcj.2019.101108

    Article  Google Scholar 

  35. Yutao, J., Wang, P., Niyato, D., & Xiong, Z. (2018). Social welfare maximization auction in edge computing resource allocation for mobile blockchain. In 2018 IEEE international conference on communications (ICC), pp. 1–6. IEEE.

    Google Scholar 

  36. Wu, Y., Wang, Z., Ma, Y., & Leung, V. C. M. (2021). Deep reinforcement learning for blockchain in industrial IoT: A survey. Computer Networks, 108004.

    Google Scholar 

  37. Wu, Y., Dai, H.-N., & Wang, H. (2020). Convergence of blockchain and edge computing for secure and scalable IIoT critical infrastructures in industry 4.0. IEEE Internet of Things Journal.

    Google Scholar 

  38. Wu, Y. (2020). Cloud-edge orchestration for the internet-of-things: Architecture and AI-powered data processing. IEEE Internet of Things Journal.

    Google Scholar 

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Acknowledgments

We would like to thank the book editors for giving us the opportunity to contribute to this timely and useful book with an interesting topic.

Author information

Authors and Affiliations

  1. Zayed University, AbuDhabi, UAE

    Jamal Al-Karaki

  2. The Hashemite University, Zarka, Jordan

    Jamal Al-Karaki

  3. Abu Dhabi Polytechnic, Abu Dhabi, UAE

    Deepa Pavithran

  4. College of Engineering and IT, University of Dubai, Dubai, UAE

    Amjad Gawanmeh

Authors
  1. Jamal Al-Karaki
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  2. Deepa Pavithran
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  3. Amjad Gawanmeh
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Corresponding author

Correspondence to Jamal Al-Karaki .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, School of Technology, Pandit Deendayal Energy University, Gandhinagar, Gujarat, India

    Chintan Bhatt

  2. Department of Computer Science, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK

    Yulei Wu

  3. Computer Sciences Department, University of Sharjah, Sharjah, United Arab Emirates

    Saad Harous

  4. Dip. di Ingegneria Civile, Universita' di Messina, Messina, Italy

    Massimo Villari

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Al-Karaki, J., Pavithran, D., Gawanmeh, A. (2022). Integrating Blockchain with Fog and Edge Computing for Micropayment Systems. In: Bhatt, C., Wu, Y., Harous, S., Villari, M. (eds) Security Issues in Fog Computing from 5G to 6G. Internet of Things. Springer, Cham. https://doi.org/10.1007/978-3-031-08254-2_6

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  • DOI: https://doi.org/10.1007/978-3-031-08254-2_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-08253-5

  • Online ISBN: 978-3-031-08254-2

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