Artificial Intelligence Driven Crypto Currencies

Authors

  • Apoorva Ganapathy Adobe Systems
  • Md. Redwanuzzaman Pabna University of Science and Technology
  • Md. Mahbubur Rahaman Leading University
  • Wahiduzzaman Khan Ahsanullah University of Science and Technology

DOI:

https://doi.org/10.18034/gdeb.v9i2.557

Keywords:

Cryptocurrency, Cryptography, Artificial Intelligence, Data Encryption, Deep Learning, Blockchain, Bitcoin

Abstract

Artificial intelligence-driven cryptocurrencies are cryptocurrencies created by Artificial intelligence using the traditional human cryptocurrency development framework without human intervention. An AI explores the data from each different stream and arriving at the framework which can host these cryptocurrencies following the standards of legality. Cryptography is the encryption of specific data to conceal it and keep it a secret from unwanted third parties. Cryptocurrencies are encrypted currencies with unique keys as developed by developers. Artificial intelligence is an advanced machine programmed to simulate and emulate human intelligence by carrying tasks and reaching conclusions with little or no human intervention. This work considered the use of AI through machine learning and deep learning in the development of cryptocurrencies. The AI machine will set all the parameters and structure of the cryptocurrency. This will include how data is added, removed, and verified on the stream. Blockchain is an open ledger of a cryptocurrency's transactions. It stores files in the system, arranged in blocks, and connected on a list called chains. The article considers how AI-driven cryptocurrency will run using the blockchain network and its impact on it. Artificial intelligence and cryptocurrency are technological very essential technological development currently. The effect of the combination of both technologies would be enormous in the future as both technologies will develop each other remarkably.

 

Downloads

Download data is not yet available.

Author Biographies

  • Apoorva Ganapathy, Adobe Systems

    Senior Developer, Adobe Systems, San Jose, California, USA

  • Md. Redwanuzzaman, Pabna University of Science and Technology

    Associate Professor, Department of Business Administration, Pabna University of Science and Technology, Pabna, BANGLADESH

  • Md. Mahbubur Rahaman, Leading University

    Assistant Professor, Department of Business Administration, Leading University, Sylhet, BANGLADESH

  • Wahiduzzaman Khan, Ahsanullah University of Science and Technology

    Associate Professor of Marketing, School of Business, Ahsanullah University of Science and Technology, Dhaka, BANGLADESH

References

Donepudi, P. K. (2018). AI and Machine Learning in Retail Pharmacy: Systematic Review of Related Literature. ABC Journal of Advanced Research, 7(2), 109-112. https://doi.org/10.18034/abcjar.v7i2.514 DOI: https://doi.org/10.18034/abcjar.v7i2.514

Donepudi, P. K. (2019). Automation and Machine Learning in Transforming the Financial Industry. Asian Business Review, 9(3), 129-138. https://doi.org/10.18034/abr.v9i3.494 DOI: https://doi.org/10.18034/abr.v9i3.494

Donepudi, P. K. (2020). Crowdsourced Software Testing: A Timely Opportunity. Engineering International, 8(1), 25-30. https://doi.org/10.18034/ei.v8i1.491 DOI: https://doi.org/10.18034/ei.v8i1.491

Donepudi, P. K., Ahmed, A. A. A., Saha, S. (2020). Emerging Market Economy (EME) and Artificial Intelligence (AI): Consequences for the Future of Jobs. Palarch’s Journal of Archaeology of Egypt/Egyptology, 17(6), 5562-5574. https://archives.palarch.nl/index.php/jae/article/view/1829

Ganapathy, A. (2017). Friendly URLs in the CMS and Power of Global Ranking with Crawlers with Added Security. Engineering International, 5(2), 87-96. https://doi.org/10.18034/ei.v5i2.541

Ganapathy, A. (2018). Cascading Cache Layer in Content Management System. Asian Business Review, 8(3), 177-182. https://doi.org/10.18034/abr.v8i3.542

Ganapathy, A. (2019). Image Association to URLs across CMS Websites with Unique Watermark Signatures to Identify Who Owns the Camera. American Journal of Trade and Policy, 6(3), 101-106. https://doi.org/10.18034/ajtp.v6i3.543

Neogy, T. K., & Paruchuri, H. (2014). Machine Learning as a New Search Engine Interface: An Overview. Engineering International, 2(2), 103-112. https://doi.org/10.18034/ei.v2i2.539

Paruchuri, H. (2015). Application of Artificial Neural Network to ANPR: An Overview. ABC Journal of Advanced Research, 4(2), 143-152. https://doi.org/10.18034/abcjar.v4i2.549

Paruchuri, H. (2017). Credit Card Fraud Detection using Machine Learning: A Systematic Literature Review. ABC Journal of Advanced Research, 6(2), 113-120. https://doi.org/10.18034/abcjar.v6i2.547

Paruchuri, H. (2018). AI Health Check Monitoring and Managing Content Up and Data in CMS World. Malaysian Journal of Medical and Biological Research, 5(2), 141-146. https://doi.org/10.18034/mjmbr.v5i2.554 DOI: https://doi.org/10.18034/mjmbr.v5i2.554

Vadlamudi, S. (2015). Enabling Trustworthiness in Artificial Intelligence - A Detailed Discussion. Engineering International, 3(2), 105-114. https://doi.org/10.18034/ei.v3i2.519

Vadlamudi, S. (2016). What Impact does Internet of Things have on Project Management in Project based Firms?. Asian Business Review, 6(3), 179-186. https://doi.org/10.18034/abr.v6i3.520

Vadlamudi, S. (2017). Stock Market Prediction using Machine Learning: A Systematic Literature Review. American Journal of Trade and Policy, 4(3), 123-128. https://doi.org/10.18034/ajtp.v4i3.521

Vadlamudi, S. (2018). Agri-Food System and Artificial Intelligence: Reconsidering Imperishability. Asian Journal of Applied Science and Engineering, 7(1), 33-42. Retrieved from https://journals.abc.us.org/index.php/ajase/article/view/1192

--0--

Downloads

Published

2020-12-31

Issue

Vol. 9 No. 2 (2020): July - December Issue

Section

Articles

License

The CC BY-NC 4.0 license lets others remix, tweak, and build upon your work non-commercially, and although their new works must also acknowledge & be non-commercial, they don’t have to license their derivative works on the same terms.
|| View License Deed ||
|| View Legal Code ||
 
Publishing paper with Global Disclosure in Economics and Business means that the author or authors retain the copyright in the paper.
This journal is granted an exclusive noncommercial reuse license by the author(s), but the author(s) are able to put the paper onto a website, distribute it to colleagues, give it to students, use it in your thesis, etc, so long as the use is not directed at commercial advantage or toward private monetary gain.
The author(s) can reuse the figures and tables and other information contained in their paper published by Global Disclosure in Economics and Business in future papers or work without having to ask anyone for permission, provided that the figures, tables or other information that is included in the new paper or work properly references the published paper as the source of the figures, tables or other information, and the new paper or work is not direct at private monetary gain or commercial advantage.

How to Cite

Ganapathy, A., Redwanuzzaman, M. ., Rahaman, M. M., & Khan, W. (2020). Artificial Intelligence Driven Crypto Currencies. Global Disclosure of Economics and Business, 9(2), 107-118. https://doi.org/10.18034/gdeb.v9i2.557
Crossref
Scopus
Google Scholar
Europe PMC

Similar Articles

11-20 of 83

You may also start an advanced similarity search for this article.