Quantum Entanglement-Assisted Adaptive Firewall Intelligence for Sustainable Next-Generation Cybersecurity

This paper presents Quantum Entanglement-Assisted Adaptive Firewall Intelligence (QEAFIS), a novel three-tier cybersecurity framework that integrates quantum entanglement and artificial intelligence to enhance threat detection in next-generation hybrid classical–quantum networks. The proposed system employs Entanglement-Guided Inter-Packet Correlation, Behavioral Fingerprint Memory, and Dynamic Quantum Threshold Adaptation to identify advanced persistent, polymorphic, and zero-day attacks while continuously adapting to evolving cyber threats. Experimental evaluation on benchmark datasets and real-world deployment demonstrates superior performance, achieving 98.4% unknown threat detection accuracy, significantly reducing false positives and response latency compared to existing classical and quantum-based approaches, thereby providing a scalable, intelligent, and sustainable solution for next-generation cybersecurity.