Identifying patterns and mechanisms of AI integration in blockchain for e-voting network security

Authors

DOI:

https://doi.org/10.15587/1729-4061.2024.305696

Keywords:

artificial intelligence, blockchain, network security, smart contracts, e-voting, optimization

Abstract

The study focuses on the enhancement of e-voting blockchain network security through the integration of artificial intelligence. The critical problem addressed is the existing limitations in real-time threat detection and anomaly detection within blockchain transactions. These limitations can compromise the integrity and security of blockchain networks, making them vulnerable to attacks and fraudulent activities.

The core results of the research include the development and implementation of sophisticated AI algorithms designed to enhance the monitoring of blockchain transactions and the auditing of smart contracts. These AI-driven advancements introduce unique features, such as the capability to detect and respond to security threats and anomalies in real-time. This significantly strengthens and optimizes the security frameworks of blockchain systems in e-voting. These results are explained by the strategic application of machine learning and natural language processing methodologies. By employing these advanced AI techniques, the study has achieved more accurate and efficient threat detection, thereby addressing the security challenges previously mentioned.

The practical applications of these findings are extensive and diverse. Enhanced security mechanisms can be utilized in financial transactions, supply chain management, and decentralized applications, providing a robust framework for improved blockchain-based e-voting security. In conclusion, integrating AI into blockchain security mechanisms addresses current limitations in threat detection and offers a scalable and effective solution for future security challenges

Supporting Agency

  • As authors of this article, we would like to express our sincere gratitude to the Department of Information Technology at Kazakh University of Technology and Business for their invaluable support and resources throughout the course of this research. The facilities and infrastructure provided by the department were crucial for the successful completion of this project.

Author Biographies

Ainur Jumagaliyeva, K.Kulazhanov Kazakh University of Technology and Business

Senior Lecturer

Department of Information Technology

Elmira Abdykerimova, Caspian State University of Technology and Engineering named after Sh. Yessenov

Candidate of Pedagogical Sciences, Professor

Department of Computer Science

Asset Turkmenbayev, Caspian State University of Technology and Engineering named after Sh. Yessenov

Candidate of Pedagogical Sciences, Professor

Department of Fundamental Sciences

Bulat Serimbetov, K.Kulazhanov Kazakh University of Technology and Business

Candidate of Technical Sciences, Associate Professor

Department of Information Technology

Gulzhan Muratova, S.Seifullin Kazakh Agrotechnical Research University

Candidate of Physical and Mathematical Sciences

Department of Information Technology

Zauresh Yersultanova, Non-Profit Limited Company "Akhmet Baitursynuly Kostanay Regional University"

Candidate of Technical Science, Acting Associate Professor

Department of Physics, Mathematics and Digital Technology

Zhomart Zhiyembayev, Zhetysu University named after Ilyas Zhansugurov

Candidate of Physical and Mathematical Sciences

Department of Mathematics and Computer Science

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Identifying patterns and mechanisms of AI integration in blockchain for e-voting network security

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Published

2024-08-30

How to Cite

Jumagaliyeva, A., Abdykerimova, E., Turkmenbayev, A., Serimbetov, B., Muratova, G., Yersultanova, Z., & Zhiyembayev, Z. (2024). Identifying patterns and mechanisms of AI integration in blockchain for e-voting network security. Eastern-European Journal of Enterprise Technologies, 4(2 (130), 6–18. https://doi.org/10.15587/1729-4061.2024.305696

Issue

Vol. 4 No. 2 (130) (2024): Information technology. Industry control systems

Section

Information technology

License

Copyright (c) 2024 Ainur Jumagaliyeva, Elmira Abdykerimova, Asset Turkmenbayev, Bulat Serimbetov, Gulzhan Muratova, Zauresh Yersultanova, Zhomart Zhiyembayev

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