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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM62212
Volume:
10 |
4 |
April 2026
Pages:
1-9
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Amity Institute of information Technology
Amity university Raipur Chhattisgarh
Amity Institute of information Technology
Amity university Raipur Chhattisgarh
Amity Institute of information Technology
Amity university Raipur Chhattisgarh
Amity Institute of information Technology
Amity university Raipur Chhattisgarh
Amity Institute of information Technology
Amity university Raipur Chhattisgarh
Quantum computing advances rapidly and brings significant risks to traditional methods of encrypting data. As a result, new and innovative methods must be designed to provide advanced security techniques that will defend against both classical and quantum-based attacks. This work explores an AI-assisted hybrid cryptographic architecture (HCA) that combines traditional encryption, post-quantum methods of data encryption, and artificial intelligence to create a more secure system than offered by any of the individual methods alone. The HCA uses Algorithm 1, which applies an adaptive key management and threat detection protocol utilizing classical and lattice-based cryptographic techniques to create a unified hybrid key that provides dual layers of security. The HCA uses AI-assisted anomaly detection to monitor system functions, identify threats, and adjust security models accordingly. The HCA employs efficient key creation, encrypting, and decrypting processes with lower computational requirements and optimized resource usage. The performance of the HCA is evaluated against several performance metrics consisting of security level, computational complexity, total memory utilized, energy consumed, scalability, accuracy of detection, and false positive rate. The performance metrics demonstrate that the HCA significantly outperforms existing methods by achieving higher levels of security, shorter amounts of time to process information, and greater quality of detection while generating fewer false positives. The integration of AI into the HCA allows for greater adaptation to new and evolving cyber threats to respond in real time.As confirmed by both tables and graphical diagrams, the framework's proposed solution successfully balances security, efficiency, and scalability. This places it in a position to be used in today's climate of modern technologies (cloud computing, IoT networks, and secure communications). Overall, this study offers an effective and future-oriented way to deal with the obstacles of cyberspace security presented by quantum computing.
KEYWORDS
An AI-powered hybrid cryptography framework for dealing with the threats of quantum computing to conventional security has been developed using artificial intelligence (AI) due to the rapid developments in quantum computing technology and its potential to compromise conventional security methods; thus, researchers need to explore new methods of protecting their information and communications against any intentional threats from quantum computing. A result of combining AI and traditional cryptography with post-quantum cryptography produces a resilient method for both present and future cyber threats through the use of AI in the ability to detect anomalies, provide adaptive learning, and support decision-making in real-time enable the proposed hybrid cryptosystem to be highly robust and responsive to continuous changes in cyber threat environments.Algorithm 1, which is proposed by the authors as an example of the method and framework, illustrates how key generation, hybrid key exchange, encryption, and dynamic key management can be implemented through an efficient mechanism for secure communication, which will enable the development of a monitor and optimization and evaluation of the performance of the cryptographic techniques proposed for achieving secure communications.The results of the performance evaluations conducted on the proposed framework demonstrate that it provides better overall results than other current methods for the following evaluation parameters: (a) strength of security; (b) computation efficiency; (c) scalability; and (d) detection accuracy, with much lower resource consumption and much lower false positives compared to other current methods.The benefits of using hybrid cryptography for mitigating the disadvantages of individual cryptographic techniques combined with the advantages of AI in improving the capability of the system to detect and respond to continually evolving threats creates an adaptable and scalable cryptographic framework for a variety of applications, including cloud computing, the Internet of Things (IoT), and secure data transmissions.
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Publication Date
5/2/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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