Neuro-Driven Agent-Based Security for Quantum-Safe 6G Networks

Mohammed Alwakeel ()
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Mohammed Alwakeel: Computer Engineering Department, Faculty of Computers and Information Technology, University of Tabuk, Tabuk 71491, Saudi Arabia

Mathematics, 2025, vol. 13, issue 13, 1-34

Abstract: Around the same time that 6G networks will be launched, advances in quantum computing could challenge existing cryptographic security. This study provides a new approach for designing a quantum-safe 6G security architecture powered by neurons. The framework uses connected cognitive agents that apply neuro-symbolic learning to respond quickly to any quantum-based security threats that may appear in network slices. Experiments carried out using simulations across various network setups with different threats verify that the presented method improves the detection rate of quantum attacks by 37.8%, uses 29.2% less communication capacity than other methods in the field. This network includes features that strengthen it to resist quantum decryption, while at the same time keeping replies fast enough for 6G. When using specific quantum-inspired techniques, accomplishing tasks requires only 42.5% fewer false alarms compared to other intrusion methods. With this research, people are now better prepared for quantum-protected wireless networks and 6G systems that ensure stability in the future.

Keywords: 6G security; quantum-safe networks; neuro-symbolic learning; agent-based systems; federated learning; network slicing; adversarial training (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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