An Adaptive Quantum Key Distribution Framework Using Fuzzy Reinforcement Learning for Secure Communication
D. Nagarajan, J C Kavitha, D Subitha
Quantum Key Distribution (QKD) has the main advantage of providing unconditional security, which is a consequence of the fundamental principles of quantum mechanics. For decades, key quantum distribution system has been the technological heart of security systems. However, the existing real QKD approaches have performance limitations. The channel experiences interference, photon loss, and fluctuations in eavesdropping conditions that reduce the efficiency and reliability of key generation. To address these issues, a fuzzy reinforcement learning-enhanced quantum key distribution (FRL-QKD) system is proposed to obtain secure and adaptable quantum communications. The integrated network combines fuzzy logic with reinforcement learning (RL) to expedite the localization of the photon polarization basis selection, control of key rates, and identification of error correction thresholds for optimized key generation. Fuzzy inference mechanisms are utilized within the FRL-QKD model to interpret an ambiguous environment. This first-stage implementation of the symbiosis of quantum cryptography, fuzzy intelligence and adaptive learning is a potent resource for future quantum-secure communications.
International Conference on Next-Gen Quantum and Advanced Computing: Algorithms, Security, and Beyond (NQComp)•Mar 5, 2026•0 citations