Overview of Applied Data Analytic Mechanisms and Approaches Using Permissioned Blockchains

Muhyidean Altarawneh, Mohammad Qatawneh, Wesam Almobaideen


Blockchain technology deployment has surged in diverse domains to secure and maintain valuable data. Wherever valuable data exists, the motivation of applying analytics emerges. However, this case is slightly different since it deals with a distributed system environment with security constraints such as privacy and confidentiality. This study aims to provide an overview of approaches that applied analytics over permissioned blockchains. Moreover, extract key features from these studies to report and discuss common features and best practices. This contributes to determining the requirements to apply analytics and outlines the remaining challenges. The research method was conducted in four phases. The initial phase states the goals and objectives. Subsequently, the analysis phase examines a group of research papers to extract key features from various studies. These features were divided into three categories: general aspects, data management, and an analytics perspective. Afterward, the outcomes are classified according to the findings and observations to point out common aspects and best practices. Finally, the evaluation of the research determines the requirements to apply data analytics over permissioned blockchains. Based on the findings and observations of these research papers. Most of the studies focused on off-chain analytics with the assistance of a third party. Also, most of the analytics types were descriptive and diagnostic, whereas fewer studies proposed predictive analytics. This explains the lack of existing approaches that use artificial intelligence and real-time analysis. The most used blockchain platform for analytics was Hyperledger fabric for multiple reasons mentioned in detail in this research.


Blockchain; permissioned blockchain; Hyperledger fabric; data analytics.

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E. Androulaki et al., “Hyperledger fabric: a distributed operating system for permissioned blockchains,†in Proceedings of the Thirteenth EuroSys Conference, 2018, pp. 1–15.

R. Yang, F. R. Yu, P. Si, Z. Yang, and Y. Zhang, “Integrated blockchain and edge computing systems: A survey, some research issues and challenges,†IEEE Commun. Surv. Tutorials, vol. 21, no. 2, pp. 1508–1532, 2019.

N. Afiza, M. Razali, W. Nurhidayat, and W. Muhamad, “Secure Blockchain-Based Data-Sharing Model and Adoption among Intelligence Communities,†vol. 48, no. 1, 2021.

S. Akter, K. Michael, M. R. Uddin, G. McCarthy, and M. Rahman, “Transforming business using digital innovations: the application of AI, blockchain, cloud and data analytics,†Ann. Oper. Res., 2020, doi: 10.1007/s10479-020-03620-w.

W. Viriyasitavat, T. Anuphaptrirong, and D. Hoonsopon, “When blockchain meets internet of things: characteristics, challenges, and business opportunities,†J. Ind. Inf. Integr., 2019.

H. T. Vo, M. Mohania, D. Verma, and L. Mehedy, “Blockchain-powered big data analytics platform,†in International Conference on Big Data Analytics, 2018, pp. 15–32.

H. K. Saadeh, W. Almobaideen, and K. E. Sabri, “PPUSTMAN: Privacy-Aware PUblish/Subscribe IoT MVC Architecture Using Information Centric Networking,†Mod. Appl. Sci., vol. 12, no. 5, p. 128, 2018.

Z. Zheng, S. Xie, H.-N. Dai, X. Chen, and H. Wang, “Blockchain challenges and opportunities: A survey,†Int. J. Web Grid Serv., vol. 14, no. 4, pp. 352–375, 2018.

S. Tanwar, Q. Bhatia, P. Patel, A. Kumari, P. K. Singh, and W. C. Hong, “Machine Learning Adoption in Blockchain-Based Smart Applications: The Challenges, and a Way Forward,†IEEE Access, vol. 8, pp. 474–448, 2020, doi: 10.1109/ACCESS.2019.2961372.

T. M. Fernández-Caramés and P. Fraga-Lamas, “A Review on the Use of Blockchain for the Internet of Things,†IEEE Access, vol. 6, pp. 32979–33001, 2018, doi: 10.1109/ACCESS.2018.2842685.

K. Salah, M. H. U. Rehman, N. Nizamuddin, and A. Al-Fuqaha, “Blockchain for AI: Review and open research challenges,†IEEE Access, vol. 7, pp. 10127–10149, 2019.

K. Heister, Stanton and Kaufmann, Matthew and Yuthas, “Blockchain and the future of business data analyticsBlockchain business data,†J. Emerg. Technol. Account., 2020.

T. Hewa, G. Gur, A. Kalla, M. Ylianttila, A. Bracken, and M. Liyanage, “The role of blockchain in 6G: Challenges, opportunities and research directions,†2nd 6G Wirel. Summit 2020 Gain Edge 6G Era, 6G SUMMIT 2020, pp. 4–8, 2020, doi: 10.1109/6GSUMMIT49458.2020.9083784.

M. Moniruzzaman, S. Khezr, A. Yassine, and R. Benlamri, “Blockchain for smart homes: Review of current trends and research challenges,†Comput. Electr. Eng., vol. 83, no. February, p. 106585, 2020, doi: 10.1016/j.compeleceng.2020.106585.

P. Z. Weilin Zheng, Zibin Zheng , Hong-Ning Dai , Xu Chen, “XBlock-EOS: Extracting and exploring blockchain data from EOSIO,†Inf. Process. Manag., vol. 58, no. 3, 2021, [Online]. Available: https://doi.org/10.1016/j.ipm.2020.102477.

V. J. Morkunas, J. Paschen, and E. Boon, “How blockchain technologies impact your business model,†Bus. Horiz., vol. 62, no. 3, pp. 295–306, 2019, doi: 10.1016/j.bushor.2019.01.009.

J. Polge, J. Robert, and Y. Le Traon, “Permissioned blockchain frameworks in the industry: A comparison,†ICT Express, 2020, doi: 10.1016/j.icte.2020.09.002.

M. Nofer, P. Gomber, O. Hinz, and D. Schiereck, “Blockchain,†Bus. Inf. Syst. Eng., vol. 59, no. 3, pp. 183–187, 2017, doi: 10.1007/s12599-017-0467-3.

S. Nakamoto and others, “Bitcoin: A peer-to-peer electronic cash system.(2008).†2008.

H. Halaburda, “Blockchain revolution without the blockchain?,†Commun. ACM, vol. 61, no. 7, pp. 27–29, 2018, doi: 10.1145/3225619.

M. Niranjanamurthy, B. N. Nithya, and S. Jagannatha, “Analysis of Blockchain technology: pros, cons and SWOT,†Cluster Comput., vol. 22, no. 2, pp. 14743–14757, 2019, doi: 10.1007/s10586-018-2387-5.

S. Y. Lim et al., “Blockchain technology the identity management and authentication service disruptor: A survey,†Int. J. Adv. Sci. Eng. Inf. Technol., vol. 8, no. 4–2, pp. 1735–1745, 2018, doi: 10.18517/ijaseit.8.4-2.6838.

O. Abualghanam, M. Qatawneh, and W. Almobaideen, “A survey of key distribution in the context of internet of things,†J. Theor. Appl. Inf. Technol., vol. 97, no. 22, 2019.

W. Almobaideen and M. Altarawneh, “Fog computing: Survey on decoy information technology,†Int. J. Secur. Networks, vol. 15, no. 2, pp. 111–121, 2020, doi: 10.1504/IJSN.2020.106833.

M. K. Saggi and S. Jain, “A survey towards an integration of big data analytics to big insights for value-creation,†Inf. Process. Manag., vol. 54, no. 5, pp. 758–790, 2018, doi: 10.1016/j.ipm.2018.01.010.

V. Grover, R. H. L. Chiang, T.-P. Liang, and D. Zhang, “Creating strategic business value from big data analytics: A research framework,†J. Manag. Inf. Syst., vol. 35, no. 2, pp. 388–423, 2018.

M. M. Najafabadi, F. Villanustre, T. M. Khoshgoftaar, N. Seliya, R. Wald, and E. Muharemagic, “Deep learning applications and challenges in big data analytics,†J. Big Data, vol. 2, no. 1, p. 1, 2015.

Y. Duan, J. S. Edwards, and Y. K. Dwivedi, “Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda,†Int. J. Inf. Manage., vol. 48, no. January, pp. 63–71, 2019, doi: 10.1016/j.ijinfomgt.2019.01.021.

M. G. Kibria, K. Nguyen, G. P. Villardi, O. Zhao, K. Ishizu, and F. Kojima, “Big data analytics, machine learning, and artificial intelligence in next-generation wireless networks,†IEEE access, vol. 6, pp. 32328–32338, 2018.

N. O. Nawari and S. Ravindran, “Blockchain and the built environment: Potentials and limitations,†J. Build. Eng., vol. 25, no. October 2018, 2019, doi: 10.1016/j.jobe.2019.100832.

Q. Nasir, I. A. Qasse, M. Abu Talib, and A. B. Nassif, “Performance analysis of hyperledger fabric platforms,†Secur. Commun. Networks, vol. 2018, 2018.

X. Xu, G. Sun, L. Luo, H. Cao, H. Yu, and A. V. Vasilakos, “Latency performance modeling and analysis for hyperledger fabric blockchain network,†Inf. Process. Manag., vol. 58, no. 1, p. 102436, 2021, doi: 10.1016/j.ipm.2020.102436.

G. T. Nguyen and K. Kim, “A survey about consensus algorithms used in Blockchain,†J. Inf. Process. Syst., vol. 14, no. 1, pp. 101–128, 2018, doi: 10.3745/JIPS.01.0024.

Z. Li, Z. Xiao, Q. Xu, E. Sotthiwat, R. S. M. Goh, and X. Liang, “Blockchain and IoT Data Analytics for Fine-Grained Transportation Insurance,†in 2018 IEEE 24th International Conference on Parallel and Distributed Systems (ICPADS), 2018, pp. 1022–1027.

K. Lampropoulos, G. Georgakakos, and S. Ioannidis, “Using Blockchains to Enable Big Data Analysis of Private Information,†in 2019 IEEE 24th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), 2019, pp. 1–6.

N. B. Somy et al., “Ownership Preserving AI Market Places Using Blockchain,†in 2019 IEEE International Conference on Blockchain (Blockchain), 2019, pp. 156–165.

K. Sarpatwar, V. Sitaramagiridharganesh Ganapavarapu, K. Shanmugam, A. Rahman, and R. Vaculin, “Blockchain enabled AI marketplace: The price you pay for trust,†in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019, p. 0.

A. Juneja and M. Marefat, “Leveraging blockchain for retraining deep learning architecture in patient-specific arrhythmia classification,†in 2018 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), 2018, pp. 393–397.

O. Attia, I. Khoufi, A. Laouiti, and C. Adjih, “An IoT-Blockchain Architecture Based on Hyperledger Framework for Healthcare Monitoring Application,†in 2019 10th IFIP International Conference on New Technologies, Mobility and Security (NTMS), 2019, pp. 1–5.

S. Rasool, M. Iqbal, T. Dagiuklas, Z. Ul-Qayyum, and S. Li, “Reliable data analysis through blockchain based crowdsourcing in mobile ad-hoc cloud,†Mob. Networks Appl., vol. 25, no. 1, pp. 153–163, 2020.

B. Nasrulin, M. Muzammal, and Q. Qu, “Chainmob: Mobility analytics on blockchain,†in 2018 19th IEEE International Conference on Mobile Data Management (MDM), 2018, pp. 292–293.

E. Zhou, H. Sun, B. Pi, J. Sun, K. Yamashita, and Y. Nomura, “Ledgerdata Refiner: A Powerful Ledger Data Query Platform for Hyperledger Fabric,†in 2019 Sixth International Conference on Internet of Things: Systems, Management and Security (IOTSMS), 2019, pp. 433–440.

D. N. Dillenberger et al., “Blockchain analytics and artificial intelligence,†IBM J. Res. Dev., vol. 63, no. 2/3, pp. 1–5, 2019.

M. Salimitari, M. Joneidi, and M. Chatterjee, “Ai-enabled blockchain: An outlier-aware consensus protocol for blockchain-based iot networks,†in 2019 IEEE Global Communications Conference (GLOBECOM), 2019, pp. 1–6.

C. Schaefer and C. Edman, “Transparent Logging with Hyperledger Fabric,†in 2019 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), 2019, pp. 65–69.

P. Novotny et al., “Permissioned blockchain technologies for academic publishing,†Inf. Serv. & Use, vol. 38, no. 3, pp. 159–171, 2018.

M. Abraham, H. Aithal, and K. Mohan, “Real time Smart Contracts for IoT using Blockchain and Collaborative Intelligence based Dynamic Pricing for the next generation Smart Toll Application,†arXiv Prepr. arXiv2002.12654, 2020.

DOI: http://dx.doi.org/10.18517/ijaseit.12.1.12827


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