Authors :
Sapna Bhimajiyani
Volume/Issue :
Volume 9 - 2024, Issue 10 - October
Google Scholar :
https://tinyurl.com/3ryas9xa
Scribd :
https://tinyurl.com/nxfkj262
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24OCT188
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
The fragility of conventional blockchain
systems is becoming more apparent in face of the relentless
march forward in quantum computing. In this paper, we
suggest the optimal architecture for quantum-resistant
blockchains deploying AI regarding consensus self-
evolving security protocols and mechanisms. An intuitive
example of this integration is the use of machine learning
algorithms for a self-adapting security system, which
automatically adjusts the protection on its infrastructure
capabilities to evolving quantum threats. In this paper, we
address the consequences of quantum computing in
blockchain security introduce a framework for AI-assisted
consensus (Section 3) and cover the feasibility of self-
evolving blockchains that guarantee their reliability as well
as integrity in a post-quantum era.
Keywords :
Blockchain, Security Upgrades, integrity, Quantum Computing, , Artificial intelligence, Consensus Mechanism , Self-Evolving Systems.
References :
- Chen, L. K., & Zhang, S. (2017). Post-quantum cryptography: Current status and future directions. *Cryptography Journal*.
- Shore, P.S. W. (1997). Polynomial-time algorithms for prime factorization and discrete logarithms in quantum computers. *SIAM Research*.
- Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic currency system. *Bitcoin.org link*.
- Bhatt, C., & Kaur, A. (2019). Quantum cryptography: The future of secure communications. *International Journal of Computer Management*.
- Zhang, H., and Wu, J. (2020). AI-driven concepts in blockchain: A review. *IEEE Transactions on Neural Networks and Learning Systems*.
The fragility of conventional blockchain
systems is becoming more apparent in face of the relentless
march forward in quantum computing. In this paper, we
suggest the optimal architecture for quantum-resistant
blockchains deploying AI regarding consensus self-
evolving security protocols and mechanisms. An intuitive
example of this integration is the use of machine learning
algorithms for a self-adapting security system, which
automatically adjusts the protection on its infrastructure
capabilities to evolving quantum threats. In this paper, we
address the consequences of quantum computing in
blockchain security introduce a framework for AI-assisted
consensus (Section 3) and cover the feasibility of self-
evolving blockchains that guarantee their reliability as well
as integrity in a post-quantum era.
Keywords :
Blockchain, Security Upgrades, integrity, Quantum Computing, , Artificial intelligence, Consensus Mechanism , Self-Evolving Systems.