Integration of artificial intelligence in cyber security systems to counter quantum computing threats - Ekowati, Maria Atik Sunarti; Poernomo, Moyo Hady; Nindyatama, Zefanya Permata (Jurnal Mandiri IT, 2025)
With the rapid advancement in quantum computing, threats to cybersecurity systems are increasingly complex, especially in terms of encryption and data protection. The integration of artificial intelligence (AI) into cybersecurity systems is essential to address these challenges. This study aims to examine the potential of AI in improving the detection and mitigation capabilities of threats arising from the quantum computing revolution. The urgency of this research is driven by the prediction that existing cryptographic algorithms will be easily cracked by quantum computers, raising the need for more adaptive and dynamic security systems. The method used in this study is a simulation approach using machine learning algorithms to model and identify cyber threat patterns specific to quantum computing. The results show that AI-based systems can detect attacks faster and with higher accuracy compared to conventional systems. The output of this research is the development of a security system prototype that combines artificial intelligence and post-quantum security technologies, which can be implemented in various cyber applications to ensure more effective data protection in the quantum computing era.