Empowering Metaverse Through Machine Learning and Blockchain Technology: A Study on Machine Learning, Blockchain, and Their Combination to Enhance Metaverse

The Metaverse is an innovative world grasping the attention of many users seeking this trend. With the trending use of Blockchain technology emerging in client-based applications, there has been a call for the empowerment of Metaverse applications through the combination of Blockchain and Artificial Intelligence. This research paper aims to propose strategies for addressing the security concerns and the user-friendliness of Metaverse applications by fusing Blockchain technology with Machine Learning concepts like Linear Regression, Artificial Neural Networks, Deep Learning, and Recommender Systems. The first proposed strategy aims to enhance security and predict malicious attacks on Blockchain user transactions in Metaverse worlds through Linear Regression and Artificial Neural Networks. The second proposed strategy pursues the creation of a Content-Based Filtering Recommendation System of Blockchain assets for Metaverse users to purchase. The expected outcome will result in a more secure and intelligent Metaverse world for user participation.

Content

Author and article information

Journal

Title: ScienceOpen Preprints

Publisher: ScienceOpen

Publication date (Electronic preprint): 2 July 2022

Affiliations

[1 ] Department of Computer Science, Faculty of Arts and Sciences, University of Balamand, Balamand el Koura, North Governate, Lebanon

Author notes

[* ]Email: ghantousnad@ 123456gmail.com .

Author information

Nad Ghantous https://orcid.org/0000-0003-0252-7378

Article

DOI: 10.14293/S2199-1006.1.SOR-.PP97BSJ.v1

SO-VID: ee76c294-6087-4a19-93fb-d1af30a87cf0

License:

This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .

History

Date received : 2 July 2022

Data availability: Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

ScienceOpen disciplines: Software engineering,Computer science,Artificial intelligence

Keywords: Metaverse,Linear Regression,Artificial Neural Networks,Blockchain,Recommender Systems

References

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Shahbazi Zeinab, Byun Yung-Cheol. Integration of Blockchain, IoT and Machine Learning for Multistage Quality Control and Enhancing Security in Smart Manufacturing. Sensors. Vol. 21(4)2021. MDPI AG. [Cross Ref]
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Comments

Comment on this article

[1] Chatterjee Ayan, Shahaab Ali, Gerdes Martin W., Martinez Santiago, Khatiwada Pankaj. Leveraging technology for healthcare and retaining access to personal health data to enhance personal health and well-beingRecent Trends in Computational Intelligence Enabled Research. p. 367–376. 2021. Elsevier. [Cross Ref]

[2] Yassine AFOUDI, Mohamed LAZAAR, Al Achhab Mohammed. Intelligent recommender system based on unsupervised machine learning and demographic attributes. Simulation Modelling Practice and Theory. Vol. 107:2021. Elsevier BV. [Cross Ref]

[3] Xu Ankun, Chang Huimin, Xu Yingjie, Li Rong, Li Xiang, Zhao Yan. Applying artificial neural networks (ANNs) to solve solid waste-related issues: A critical review. Waste Management. Vol. 124:385–402. 2021. Elsevier BV. [Cross Ref]

[4] Wang Gang, Nixon Mark. SoK. Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion. 2021. ACM. [Cross Ref]

[5] Umar Muhammad, Su Chi-Wei, Rizvi Syed Kumail Abbas, Shao Xue-Feng. Bitcoin: A safe haven asset and a winner amid political and economic uncertainties in the US? Technological Forecasting and Social Change. Vol. 167:2021. Elsevier BV. [Cross Ref]

[6] Shahbazi Zeinab, Byun Yung-Cheol. Integration of Blockchain, IoT and Machine Learning for Multistage Quality Control and Enhancing Security in Smart Manufacturing. Sensors. Vol. 21(4)2021. MDPI AG. [Cross Ref]

[7] Nyarko‐Boateng Owusu, Adekoya Adebayo Felix, Weyori Benjamin Asubam. Predicting the actual location of faults in underground optical networks using linear regression. Engineering Reports. Vol. 3(3)2021. Wiley. [Cross Ref]

[8] Mystakidis Stylianos. Metaverse. Encyclopedia. Vol. 2(1):486–497. 2022. MDPI AG. [Cross Ref]

[9] May Mike. Eight ways machine learning is assisting medicine. Nature Medicine. Vol. 27(1):2–3. 2021. Springer Science and Business Media LLC. [Cross Ref]

[10] Kwekha-Rashid Ameer Sardar, Abduljabbar Heamn N., Alhayani Bilal. Coronavirus disease (COVID-19) cases analysis using machine-learning applications. Applied Nanoscience. 2021. Springer Science and Business Media LLC. [Cross Ref]

[11] Kim Jooyoung. Advertising in the Metaverse: Research Agenda. Journal of Interactive Advertising. Vol. 21(3):141–144. 2021. Informa UK Limited. [Cross Ref]

[12] Kirbac Gokhan, Tektas Berna. The Role of Blockchain Technology in Ensuring Digital Transformation for Businesses: Advantages, Challenges and Application Steps. The 7th International Management Information Systems Conference. 2021. MDPI. [Cross Ref]

[13] Kanade Prakash, Prasad Jai Prakash. Arduino based Machine Learning and IoT Smart Irrigation System. International Journal of Soft Computing and Engineering. Vol. 10(4):1–5. 2021. Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP. [Cross Ref]

[14] Jeon Hyun-joo, Youn Ho-chang, Ko Sang-mi, Kim Tae-heon. Blockchain and AI Meet in the MetaverseBlockchain Potential in AI. 2022. IntechOpen. [Cross Ref]

[15] Hamid Rula A., Albahri A.S., Alwan Jwan K., Al-qaysi Z.T., Albahri O.S., Zaidan A.A., Alnoor Alhamzah, Alamoodi A.H., Zaidan B.B.. How smart is e-tourism? A systematic review of smart tourism recommendation system applying data management. Computer Science Review. Vol. 39:2021. Elsevier BV. [Cross Ref]

[16] Dwita Mariana Christy, Ekaputra Irwan Adi, Husodo Zaäfri Ananto. Are Bitcoin and Ethereum safe-havens for stocks during the COVID-19 pandemic? Finance Research Letters. Vol. 38:2021. Elsevier BV. [Cross Ref]

[17] Dong Shi, Wang Ping, Abbas Khushnood. A survey on deep learning and its applications. Computer Science Review. Vol. 40:2021. Elsevier BV. [Cross Ref]

[18] Dogan Alican, Birant Derya. Machine learning and data mining in manufacturing. Expert Systems with Applications. Vol. 166:2021. Elsevier BV. [Cross Ref]

[19] Churcher Andrew, Ullah Rehmat, Ahmad Jawad, ur Rehman Sadaqat, Masood Fawad, Gogate Mandar, Alqahtani Fehaid, Nour Boubakr, Buchanan William J.. An Experimental Analysis of Attack Classification Using Machine Learning in IoT Networks. Sensors. Vol. 21(2)2021. MDPI AG. [Cross Ref]

[20] Benetton Matteo, Compiani Giovanni, Morse Adair. When Cryptomining Comes to Town: High Electricity-Use Spillovers to the Local Economy. SSRN Electronic Journal. Elsevier BV. [Cross Ref]

[21] Abbas Khizar, Afaq Muhammad, Ahmed Khan Talha, Song Wang-Cheol. A Blockchain and Machine Learning-Based Drug Supply Chain Management and Recommendation System for Smart Pharmaceutical Industry. Electronics. Vol. 9(5)2020. MDPI AG. [Cross Ref]