Journal of Information Processing Systems

Korea Information Processing Society (한국정보처리학회)
권호 표지
DOI QR코드

DOI QR Code

A Novel Smart Contract based Optimized Cloud Selection Framework for Efficient Multi-Party Computation

  • Haotian Chen (Dept. of Computer Science and Engineering, Seoul National University of Science and Technology) ;
  • Abir EL Azzaoui (Dept. of Computer Science and Engineering, Seoul National University of Science and Technology) ;
  • Sekione Reward Jeremiah (Dept. of Computer Science and Engineering, Seoul National University of Science and Technology) ;
  • Jong Hyuk Park (Dept. of Computer Science and Engineering, Seoul National University of Science and Technology)
  • Received : 2022.11.22
  • Accepted : 2023.03.02
  • Published : 2023.04.30
Download PDF
⟨ Previous Next ⟩

Abstract

The industrial Internet of Things (IIoT) is characterized by intelligent connection, real-time data processing, collaborative monitoring, and automatic information processing. The heterogeneous IIoT devices require a high data rate, high reliability, high coverage, and low delay, thus posing a significant challenge to information security. High-performance edge and cloud servers are a good backup solution for IIoT devices with limited capabilities. However, privacy leakage and network attack cases may occur in heterogeneous IIoT environments. Cloud-based multi-party computing is a reliable privacy-protecting technology that encourages multiparty participation in joint computing without privacy disclosure. However, the default cloud selection method does not meet the heterogeneous IIoT requirements. The server can be dishonest, significantly increasing the probability of multi-party computation failure or inefficiency. This paper proposes a blockchain and smart contract-based optimized cloud node selection framework. Different participants choose the best server that meets their performance demands, considering the communication delay. Smart contracts provide a progressive request mechanism to increase participation. The simulation results show that our framework improves overall multi-party computing efficiency by up to 44.73%.

Keywords

Acknowledgement

This study was supported by the Research Program funded by SeoulTech (Seoul National University of Science and Technology).

References

  1. Alliance Virtual Offices, "Working from home increases cyberattack frequency by 238%, new study by alliance virtual offices finds," 2022 [Online]. Available: https://www.globenewswire.com/en/news-release/2022/03/15/2403837/0/en/Working-From-Home-Increases-Cyberattack-Frequency-by-238-New-Study-by-Alliance-Virtual-Offices-Finds.html.
  2. A. El Azzaoui, M. Y. Choi, C. H. Lee, and J. H. Park, "Scalable lightweight blockchain-based authentication mechanism for secure VoIP communication," Human-centric Computing and Information Sciences, vol. 12, article no. 8, 2022. https://doi.org/10.22967/HCIS.2022.12.008
  3. J. S. Park and J. H. Park, "Future trends of IoT, 5G mobile networks, and AI: challenges, opportunities, and solutions," Journal of Information Processing Systems, vol. 16, no. 4, pp. 743-749, 2020. https://doi.org/10.3745/JIPS.03.0146
  4. I. Sitton-Candanedo, R. S. Alonso, O. Garcia, L. Munoz, and S. Rodriguez-Gonzalez, "Edge computing, IoT and social computing in smart energy scenarios," Sensors, vol. 19, no. 15, article no. 3353, 2019. https://doi.org/10.3390/s19153353
  5. M. M. Salim, I. Kim, U. Doniyor, C. Lee, and J. H. Park, "Homomorphic encryption based privacy-preservation for IoMT," Applied Sciences, vol. 11, no. 18, article no. 8757, 2021. https://doi.org/10.3390/app11188757
  6. R. J. Hassan, S. R. Zeebaree, S. Y. Ameen, S. F. Kak, M. A. Sadeeq, Z. S. Ageed, A. Al-Zebari, and A. A. Salih, "State of art survey for IoT effects on smart city technology: challenges, opportunities, and solutions," Asian Journal of Research in Computer Science, vol. 8, no. 3, pp. 32-48, 2021. https://doi.org/10.9734/ajrcos/2021/v8i330202
  7. S. K. Singh, A. E. Azzaoui, T. W. Kim, Y. Pan, and J. H. Park, "DeepBlockScheme: a deep learning-based blockchain driven scheme for secure smart city," Human-centric Computing and Information Sciences, vol. 11, article no. 12, 2021. https://doi.org/10.22967/HCIS.2021.11.012
  8. N. Volgushev, M. Schwarzkopf, B. Getchell, M. Varia, A. Lapets, and A. Bestavros, "Conclave: secure multiparty computation on big data," in Proceedings of the 14th EuroSys Conference 2019, Dresden, Germany, 2019, pp. 1-18.
  9. H. Boyes, B. Hallaq, J. Cunningham, and T. Watson, "The industrial internet of things (IIoT): an analysis framework," Computers in Industry, vol. 101, pp. 1-12, 2018. https://doi.org/10.1016/j.compind.2018.04.015
  10. J. Cheng, W. Chen, F. Tao, and C. L. Lin, "Industrial IoT in 5G environment towards smart manufacturing," Journal of Industrial Information Integration, vol. 10, pp. 10-19, 2018. https://doi.org/10.1016/j.jii.2018.04.001
  11. Z. Zhou, X. Chen, Y. Zhang, and S. Mumtaz, "Blockchain-empowered secure spectrum sharing for 5G heterogeneous networks," IEEE Network, vol. 34, no. 1, pp. 24-31, 2020. https://doi.org/10.1109/MNET.001.1900188
  12. Y. Tian, T. Li, J. Xiong, M. Z. A. Bhuiyan, J. Ma, and C. Peng, "A blockchain-based machine learning framework for edge services in IIoT," IEEE Transactions on Industrial Informatics, vol. 18, no. 3, pp. 1918-1929, 2022. https://doi.org/10.1109/TII.2021.3097131
  13. N. Bugshan, I. Khalil, N. Moustafa, and M. S. Rahman, "Privacy-preserving microservices in industrial Internet of Things driven smart applications," IEEE Internet of Things Journal, vol. 10, no. 4, pp. 2821-2831, 2023.
  14. A. Kumari, S. Tanwar, S. Tyagi, and N. Kumar, "Blockchain-based massive data dissemination handling in IIoT environment," IEEE Network, vol. 35, no. 1, pp. 318-325, 2021. https://doi.org/10.1109/MNET.011.2000355
  15. S. Li, S. Zhao, G. Min, L. Qi, and G. Liu, "Lightweight privacy-preserving scheme using homomorphic encryption in industrial Internet of Things," IEEE Internet of Things Journal, vol. 9, no. 16, pp. 14542-14550, 2022. https://doi.org/10.1109/JIOT.2021.3066427
  16. Y. Wang, D. K. Kim, and D. Jeong, "A survey of the application of blockchain in multiple fields of financial services," Journal of Information Processing Systems, vol. 16, no. 4, pp. 935-958, 2020. https://doi.org/10.3745/JIPS.04.0185
  17. R. R. Kumar, B. Kumari, and C. Kumar, "CCS-OSSR: a framework based on hybrid MCDM for optimal service selection and ranking of cloud computing services" Cluster Computing, vol. 24, no. 2, pp. 867-883, 2021. https://doi.org/10.1007/s10586-020-03166-3
  18. C. Jatoth, G. R. Gangadharan, U. Fiore, and R. Buyya, "SELCLOUD: a hybrid multi-criteria decision-making model for selection of cloud services," Soft Computing, vol. 23, pp. 4701-4715,
  19. R. R. Kumar, S. Mishra, and C. Kumar, "A novel framework for cloud service evaluation and selection using hybrid MCDM methods," Arabian Journal for Science and Engineering, vol. 43, pp. 7015-7030, 2018. https://doi.org/10.1007/s13369-017-2975-3
  20. L. Sun, H. Dong, O. K. Hussain, F. K. Hussain, and A. X. Liu, "A framework of cloud service selection with criteria interactions," Future Generation Computer Systems, vol. 94, pp. 749-764,
  21. F. Benhamouda, S. Halevi, and T. Halevi, "Supporting private data on Hyperledger fabric with secure multiparty computation," IBM Journal of Research and Development, vol. 63, no. 2/3, article no. 3, 2019. https://doi.org/10.1147/JRD.2019.2913621
  22. H. Gao, Z. Ma, S. Luo, and Z. Wang, "BFR-MPC: a blockchain-based fair and robust multi-party computation scheme," IEEE Access, vol. 7, pp. 110439-110450, 2019. https://doi.org/10.1109/ACCESS.2019.2934147
  23. Z. Guan, X. Zhou, P. Liu, L. Wu, and W. Yang, "A blockchain-based dual-side privacy-preserving multiparty computation scheme for edge-enabled sm