Quantum-Resilient Cognitive AI Firewall for Autonomous Smart Cities: A Federated Multi Agent Framework for Privacy Preserving Urban Cyber Defense
Abstract
This research proposes a Quantum-Resilient Cognitive AI-Enhanced Firewall (Q-CAIEF), a novel federated multi-agent cybersecurity framework designed to protect autonomous smart cities against both classical and quantum-enabled cyber threats. The framework integrates post-quantum cryptography, federated reinforcement learning, explainable AI, and privacy-preserving mechanisms to enable decentralized, intelligent, and ethical cyber defense. By combining lattice-based encryption, differential privacy, and cognitive decision-making, Q-CAIEF enhances threat detection, ensures secure collaboration among distributed agents, and maintains regulatory compliance. Experimental evaluations on large-scale smart city IoT environments demonstrate high attack detection accuracy, low latency, strong privacy protection, and resilience against quantum cryptanalytic attacks, making it a promising solution for next-generation urban cybersecurity.
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