AI-Based Authentication Mechanisms for Quantum-Resistant Cryptographic Systems in Secure Communications

Abstract

The advent of quantum computing presents a formidable challenge to traditional cryptographic systems, necessitating the development of quantum-resistant mechanisms to ensure secure communications. AI-based authentication mechanisms offer a promising solution, leveraging advanced algorithms to enhance the security and efficiency of post-quantum cryptographic systems. This paper explores the integration of AI with quantum-resistant cryptographic methods to develop robust authentication systems. Key approaches, including machine learning for anomaly detection, reinforcement learning for protocol optimization, and deep learning for biometric validation, are discussed. The study highlights the advantages of AI in identifying vulnerabilities, adapting to evolving threats, and automating secure processes. Challenges such as computational overheads, data privacy concerns, and the need for standardized frameworks are also examined. By combining AI with quantum-resistant cryptography, organizations can future-proof secure communications against quantum threats. The paper concludes with recommendations for practical implementations and future research directions to enhance global cybersecurity.