AI-Based Cryptography: A Comprehensive Review of Adaptive Encryption, Neural Cryptanalysis, and Post-Quantum Resilience

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Authors: Mohammed A. Abdewi, Farouk A. Emara, Ashraf A. Gouda, Mohammed Abdel Razek
Cited by: 1
References: 25

Abstract

Nowadays, protecting information is paramount. With the rapid evolution of cyber threats and the growing potential of quantum computing to compromise classical encryption methods, the integration of Artificial Intelligence (AI) into cryptography has become a promising area for exploration. This review outlines recent advances in AI-based encryption techniques, such as dynamic key generation, adversarial neural cryptography, and AI-enhanced cryptanalysis. It compares AI-based approaches to traditional cryptographic systems in terms of adaptability, security strength, and quantum resistance. This paper also summarizes key research contributions and highlights the benefits and current challenges of deploying AI-based cryptography, including computational overhead and the absence of formal security guarantees. The review aims to offer an introductory overview of how AI is reshaping the future of encryption and to identify areas that require further research and validation.

Fields of Study & Subjects

Adversarial Robustness in Machine Learning Chaos-based Image/Signal Encryption Cryptography and Data Security

Publication details

Journal / source
Engineering Technology & Applied Science Research
Publisher
Engineering, Technology & Applied Science Research
Volume
16
Issue
2
Pages
33790–33797
Publication date
4 April 2026