Vol. 4 No. 1 (2024): Journal of AI-Assisted Scientific Discovery
Articles

A Hybrid Model Integrating AI and Blockchain for Secure Identity Management in Decentralized Systems

PDF
  • Alexei Ivanov
Alexei Ivanov
AI Researcher, Yandex, Moscow, Russia
Cover

Published 06-02-2024

Keywords

  • AI,
  • Blockchain
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

How to Cite

[1]
A. Ivanova, “A Hybrid Model Integrating AI and Blockchain for Secure Identity Management in Decentralized Systems”, Journal of AI-Assisted Scientific Discovery, vol. 4, no. 1, pp. 253–259, Feb. 2024, Accessed: Dec. 30, 2024. [Online]. Available: https://scienceacadpress.com/index.php/jaasd/article/view/253

Abstract

In the evolving landscape of decentralized systems, ensuring secure and efficient identity management remains a challenge. Traditional centralized identity management models expose vulnerabilities to cyber threats, such as data breaches and identity theft. The integration of Artificial Intelligence (AI) and Blockchain presents a promising hybrid approach to enhance security and privacy. AI, with its advanced data processing and decision-making capabilities, can optimize identity verification processes, while Blockchain ensures transparency, immutability, and decentralization, offering a robust foundation for secure identity management. This paper explores the synergy between AI and Blockchain in decentralized systems, discussing their combined benefits, use cases, and challenges. It also proposes a framework for integrating AI and Blockchain for secure identity management and highlights potential future developments in this domain. The hybrid model presented here not only ensures enhanced privacy but also promises a seamless, user-friendly experience in managing digital identities.

PDF

Downloads

Download data is not yet available.

References

  1. Smith, J., & Roberts, T. (2023). Artificial intelligence and machine learning in identity verification. Journal of Cybersecurity, 29(4), 234-245.
  2. Miller, K., & Zhang, L. (2022). AI-driven identity federation in decentralized systems. International Journal of Blockchain Applications, 11(2), 120-134.
  3. Patel, R., & Singh, M. (2023). Blockchain-based self-sovereign identity management. Journal of Digital Privacy and Security, 19(3), 198-210.
  4. Kumar, S., & Shah, P. (2022). Decentralized identifiers for secure authentication. Journal of Blockchain Technology, 14(1), 76-89.
  5. Gupta, R., & Rao, S. (2021). Scalability and interoperability in decentralized identity systems. Blockchain and Distributed Ledger Review, 8(3), 45-56.
  6. Ali, S. A., and M. W. Zafar. "Api gateway architecture explained." INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY 6.4 (2022): 54-98.
  7. Johnson, W., & Lee, J. (2023). AI-powered anomaly detection in decentralized identity management. Cybersecurity Advances, 18(2), 89-102.
  8. Turner, F., & Harris, A. (2022). Blockchain and AI: A hybrid approach to secure identity management. International Journal of AI and Blockchain, 13(5), 190-203.
  9. Chaudhary, N., & Sharma, K. (2023). Privacy-preserving AI and Blockchain for identity management. Privacy Technology Journal, 21(6), 145-160.
  10. Wang, Q., & Xu, L. (2023). Federated learning for scalable AI in decentralized systems. AI and Privacy Journal, 11(4), 233-245.
  11. Zhang, X., & Choudhary, S. (2022). Cross-platform interoperability in Blockchain systems. Blockchain Technology Review, 16(4), 82-95.
  12. Lee, H., & Patel, S. (2021). Regulatory challenges in AI and Blockchain-based identity management. Digital Privacy and Security Journal, 7(2), 112-123.
  13. Davis, R., & Gupta, T. (2021). Zero-knowledge proofs for privacy in identity management. Journal of Cryptographic Engineering, 9(1), 58-69.
  14. Cohen, L., & Chen, Y. (2022). Enhancing identity security with Blockchain-based authentication. Journal of Cybersecurity Research, 17(3), 78-90.
  15. Patel, D., & Narayan, R. (2021). Blockchain scalability challenges in identity management. International Journal of Distributed Ledger Technologies, 22(4), 101-115.
  16. Sharma, V., & Gupta, R. (2023). AI and Blockchain for real-time fraud detection. AI and Security Journal, 20(2), 54-66.
  17. Lee, T., & Zhang, Y. (2022). Smart contracts for automated identity verification in decentralized systems. Journal of Blockchain Security, 14(3), 132-145.
  18. Kumar, S., & Agarwal, R. (2023). Machine learning for fraud detection in decentralized identity systems. International Journal of AI and Blockchain, 11(1), 44-57.
  19. Turner, S., & Harris, L. (2023). Advanced encryption techniques in Blockchain-based identity systems. Journal of Cryptography and Privacy, 19(5), 210-222.
  20. Johnson, M., & Singh, K. (2023). Blockchain-based decentralized identifiers: A future perspective. Blockchain Research Journal, 24(2), 54-67.
  21. Miller, J., & Sharma, N. (2023). Real-time anomaly detection in decentralized systems. International Journal of Cybersecurity, 9(4), 120-130.

Similar Articles

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