Utilization of Artificial Intelligence in Cyber Security System Prototype to Face Quantum Computing

Abstract

The advent of quantum computing poses significant threats to traditional cybersecurity systems, which rely on cryptographic algorithms vulnerable to quantum attacks. This research explores the utilization of artificial intelligence (AI) in designing a prototype cybersecurity system aimed at countering the emerging threats of quantum computing. The study integrates AI-based intrusion detection systems with quantum-resistant cryptographic techniques to enhance the security of digital systems against quantum-driven cyberattacks. A combination of machine learning algorithms, such as neural networks and decision trees, is employed to detect and mitigate potential cybersecurity breaches. Additionally, post-quantum cryptography (PQC) is incorporated to safeguard sensitive data against the capabilities of quantum computers. The results indicate that the proposed system outperforms conventional cybersecurity methods in detecting threats with greater speed and accuracy, while also providing robust protection against quantum-enabled attacks. Moreover, the integration of AI allows for adaptive and proactive defense mechanisms, improving the overall system resilience. The study concludes that combining AI with post-quantum cryptography offers a promising solution to secure digital infrastructures in the face of quantum computing advancements, marking a significant step toward future-proofing cybersecurity strategies.