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A Systematic Literature Review of Integration of Blockchain and Artificial Intelligence

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Blockchain Cybersecurity, Trust and Privacy

Abstract

Blockchain and artificial intelligence (AI) have gain the most research attention during recent years. Blockchain is a distributed ledger of trustworthy digital records shared by a network of participants. Blockchain technology has the potential capacity in many fields such as international payment, secure data sharing and marketing, and supply chain management. On the other side, Artificial Intelligence (AI) is used to develop the creation of machines capable of performing tasks that need intelligence.

This paper aims to determine the current state of the art within the field of AI with Blockchain technology. In particular, we investigated the latest articles on this integration and carried out an analysis to determine what applications can benefit from it. We identified 23 articles that comply with the assessment criteria. The review research demonstrates that distributed management, security and efficiency improvement, prediction and decision making are among the most popular types of applications that benefit from the integration of AI and Blockchain, while security is the hottest topic. In general, AI algorithms can improve Blockchain design and operation. The combination of these two technologies increases security, efficiency and, productivity of applications.

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Notes

  1. 1.

    https://www.zdnet.com/article/mckinsey-ai-will-create-13-trillion-in-value-by-2013/.

References

  1. S. Nakamoto, Bitcoin: a peer-to-peer electronic cash system (2018), https://bitcoin.org/bitcoin.pdf

  2. S. Homayoun, A. Dehghantanha, R.M. Parizi, K.K.R. Choo, A blockchain-based framework for detecting malicious mobile applications in app stores, in 32nd IEEE Canadian Conference of Electrical and Computer Engineering (IEEE CCECE’19). Canada (2019)

    Google Scholar 

  3. Q. Zhang, R.M. Parizi, K.K.R. Choo, A pentagon of considerations towards more secure blockchains, in IEEE Blockchain Technical Briefs (2018)

    Google Scholar 

  4. A. Yazdinejad, R.M. Parizi, A. Dehghantanha, K.K.R. Choo, Blockchain-enabled authentication handover with efficient privacy protection in SDN-based 5G networks. arXiv:1905.03193 (2019)

    Google Scholar 

  5. P. Mamoshina, L. Ojomoko, Y. Yanovich, A. Ostrovski, A. Botezatu, P. Prikhodko, A. Zhavoronkov, Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare. Oncotarget 9(5), 5665–5690 (2017)

    Google Scholar 

  6. Y. Guo, C. Liang, Blockchain application and outlook in the banking industry. Financ. Innov. 2, 24 (2016)

    Article  Google Scholar 

  7. H. Watanabe, S. Fujimura, A. Nakadaira, Y. Miyazaki, A. Akutsu, J. Kishigami, Blockchain contract: securing a blockchain applied to smart contracts, in IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NV, pp. 467–468 (2016)

    Google Scholar 

  8. S. Makridakis, A. Polemitis, G. Giaglis, S. Louca, Blockchain: the next breakthrough in the rapid progress of AI, in Artificial Intelligence-Emerging Trends and Applications (IntechOpen, 2018)

    Google Scholar 

  9. R.M. Parizi, A. Dehghantanha, On the understanding of gamification in blockchain systems, in 6th IEEE International Conference on Future Internet of Things and Cloud (FiCloud’18), Barcelona, Spain (IEEE Computer Society, 2018)

    Google Scholar 

  10. M. Koch, Artificial intelligence is becoming natural. Cell 173(3), 531–533 (2018)

    Article  Google Scholar 

  11. G. Dermody, R. Fritz, A conceptual framework for clinicians working with artificial intelligence and health-assistive smart homes. Nursing Inquiry 26, e12267 (2018)

    Article  Google Scholar 

  12. P. Agarwal, Redefining banking and financial industry through the application of computational intelligence, in 2019 Advances in Science and Engineering Technology International Conferences (ASET), Dubai, United Arab Emirates, pp. 1–5

    Google Scholar 

  13. A. Horzyk, Introduction to artificial intelligence (2018), http://home.agh.edu.pl/~horzyk/lectures/ai/aiintro.php

  14. K. Salah, M.H.U. Rehman, N. Nizamuddin, A. Al-Fuqaha, Blockchain for AI: review and open research challenges. IEEE Access 7, 10127–10149 (2019)

    Article  Google Scholar 

  15. Y. Qi, J. Xiao, Fintech: AI powers financial services to improve people’s lives. Commun. ACM 61(11), 6569 (2018)

    Article  Google Scholar 

  16. R.M. Parizi, A. Dehghantanha, Smart contract programming languages on blockchains: an empirical evaluation of usability and security, in 1st International Conference on Blockchain (ICBC’18), Seattle, USA. LNCS (Springer, 2018)

    Google Scholar 

  17. R.M. Parizi, A. Dehghantanha, K.K.R. Choo, A. Singh, Empirical vulnerability analysis of automated smart contracts security testing on blockchains, in 28th ACM Annual International Conference on Computer Science and Software Engineering (CASCON’18), Ontario, Canada (IBM, 2018)

    Google Scholar 

  18. K. Rabah, Convergence of AI, IoT, big data and blockchain: a review. Lake Inst. J. 1(1), 1–18 (2018)

    Google Scholar 

  19. B. Kitchenham, S. Charters, Guidelines for performing systematic literature reviews in software engineering. Engineering 1051(2), 1051 (2017)

    Google Scholar 

Primary Studies

  1. H. Tang, Y. Jiao, B. Huang, C. Lin, S. Goyal, B. Wang, Learning to classify blockchain peers according to their behavior sequences. IEEE Access 6, 71208–71215 (2018)

    Article  Google Scholar 

  2. A. Firdaus, N.B. Anuar, M.F. Ab Razak, I.A.T. Hashem, S. Bachok, A.K. Sangaiah, Root exploit detection and features optimization: mobile device and blockchain based medical data management. J. Med. Syst. 42(6), 112 (2018)

    Article  Google Scholar 

  3. R.Y. Chen, A traceability chain algorithm for artificial neural networks using T–S fuzzy cognitive maps in blockchain. Futur. Gener. Comput. Syst. 80, 198–210 (2018)

    Article  Google Scholar 

  4. H. Jang, J. Lee, An empirical study on modeling and prediction of bitcoin prices with Bayesian neural networks based on blockchain information. IEEE Access 6, 5427–5437 (2018)

    Article  Google Scholar 

  5. S. Dey, A proof of work: securing majority-attack in blockchain using machine learning and algorithmic game theory. Int. J. Wirel. Microwave Technol. 5, 1–9 (2018)

    Google Scholar 

  6. C. Xu, K. Wang, M. Guo, Intelligent resource management in blockchain-based cloud datacenters. IEEE Cloud Comput. 4(6), 50–59 (2017)

    Article  Google Scholar 

  7. D. Mao, F. Wang, Z. Hao, H. Li, Credit evaluation system based on blockchain for multiple stakeholders in the food supply chain. Int. J. Environ. Res. Public Health 15(8), 1627 (2018)

    Article  Google Scholar 

  8. S.H. Lee, C.S. Yang, Fingernail analysis management system using microscopy sensor and blockchain technology. Int. J. Distrib. Sens. Netw. 14(3), 1550147718767044 (2018)

    Article  Google Scholar 

  9. K. Chung, H. Yoo, D. Choe, H. Jung, Blockchain network based topic mining process for cognitive manufacturing. Wirel. Pers. Commun. 105, 583–597 (2018)

    Article  Google Scholar 

  10. J. An, D. Liang, X. Gui, H. Yang, R. Gui, X. He, Crowdsensing quality control and grading evaluation based on a two-consensus blockchain. IEEE Internet Things J. 6(3), 4711–4718 (2019)

    Article  Google Scholar 

  11. Y. Zhao, Y. Yu, Y. Li, G. Han, X. Du, Machine learning based privacy-preserving fair data trading in big data market. Inf. Sci. 478, 449–460 (2019)

    Article  Google Scholar 

  12. P. Mamoshina, L. Ojomoko, Y. Yanovich, A. Ostrovski, A. Botezatu, P. Prikhodko, I.O. Ogu, Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare. Oncotarget 9(5), 5665–5690 (2018)

    Article  Google Scholar 

  13. R. Graf, R. King, Neural network and Blockchain based technique for cyber threat intelligence and situational awareness, in 2018 10th International Conference on Cyber Conflict (CyCon) (IEEE, 2018), pp. 409–426

    Google Scholar 

  14. A. Kundu, Z. Sura, U. Sharma, Collaborative and accountable hardware governance using blockchain, in 2018 IEEE 4th International Conference on Collaboration and Internet Computing (CIC) (2018), pp. 114–121

    Google Scholar 

  15. S. Raje, S. Vaderia, N. Wilson, R. Panigrahi, Decentralised firewall for malware detection, in 2017 International Conference on Advances in Computing, Communication and Control (ICAC3) (IEEE, 2017), pp. 1–5

    Google Scholar 

  16. N.M. Ahmad, S.F.A. Razak, S. Kannan, I. Yusof, A.H.M. Amin, Improving identity management of cloud-based IoT applications using blockchain, in 2018 International Conference on Intelligent and Advanced System (ICIAS) (IEEE, 2018), pp. 1–6

    Google Scholar 

  17. X. Zheng, R.R. Mukkamala, R. Vatrapu, J. Ordieres-Mere, Blockchain-based personal health data sharing system using cloud storage, in 2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom) (IEEE, 2018), pp. 1–6

    Google Scholar 

  18. A. Juneja, 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) (IEEE, 2018), pp. 393–397

    Google Scholar 

  19. K. Singla, J. Bose, S. Katariya, Machine learning for secure device personalization using blockchain, in 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI) (IEEE, 2018), pp. 67–73

    Google Scholar 

  20. N.C. Luong, Z. Xiong, P. Wang, D. Niyato, Optimal auction for edge computing resource management in mobile blockchain networks: a deep learning approach, in 2018 IEEE International Conference on Communications (ICC) (IEEE, 2018), pp. 1–6

    Google Scholar 

  21. D. Ermilov, M. Panov, Y. Yanovich, Automatic bitcoin address clustering, in 2017 16th IEEE International Conference on Machine Learning and Applications (ICMLA) (IEEE, 2017), pp. 461–466

    Google Scholar 

  22. A. Bogner, Seeing is understanding: anomaly detection in blockchains with visualized features, in Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers (ACM, 2017), pp. 5–8

    Google Scholar 

  23. N.N. Vo, G. Xu, The volatility of bitcoin returns and its correlation to financial markets, in 2017 International Conference on Behavioral, Economic, Socio-cultural Computing (BESC) (IEEE, 2017), pp. 1–6

    Google Scholar 

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Correspondence to Haleh Amintoosi .

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Ekramifard, A., Amintoosi, H., Seno, A.H., Dehghantanha, A., Parizi, R.M. (2020). A Systematic Literature Review of Integration of Blockchain and Artificial Intelligence. In: Choo, KK., Dehghantanha, A., Parizi, R. (eds) Blockchain Cybersecurity, Trust and Privacy. Advances in Information Security, vol 79. Springer, Cham. https://doi.org/10.1007/978-3-030-38181-3_8

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  • DOI: https://doi.org/10.1007/978-3-030-38181-3_8

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