<![CDATA[RSA key generation in fifth-generation (5G) defense communication networks faces significant computational challenges due to the time-intensive search for large prime numbers, resulting in increased key generation latency and reduced operational efficiency. Existing optimization approaches based on conventional evolutionary algorithms often suffer from premature convergence and limited exploration of the prime search space. This study proposes a Quantum Inspired Genetic Algorithm (QIGA) that represents prime candidates as quantum chromosomes using probability-amplitude pairs and updates candidate solutions through a quantum rotation-gate mechanism, enabling a more diverse and efficient search than classical genetic algorithm-based RSA optimization. The proposed approach was evaluated through a controlled benchmark comprising 900 experimental observations across three RSA key sizes (1024-bit, 2048-bit, and 4096-bit), with 100 independent trials for each experimental condition, and compared against standard RSA and a classical Genetic Algorithm under identical settings. Performance was assessed using key generation latency, encryption throughput, decryption throughput, and key entropy, as these metrics collectively measure computational efficiency, cryptographic processing capability, and the randomness required for secure key generation. Experimental results demonstrate that the proposed QIGA reduced key generation latency by 40.12% and increased encryption throughput by 65.78% for 2048-bit RSA compared with the standard implementation, while producing high-quality keys with an entropy of 2041.9 bits and achieving population convergence at generation 31. These findings indicate that QIGA provides an effective and practical optimization strategy for accelerating secure RSA key generation while preserving cryptographic strength, making it suitable for low-latency, high-security defense communication systems. Future work will investigate integration with post-quantum cryptographic schemes and hardware acceleration through field-programmable gate arrays (FPGAs) for deployment in resource-constrained tactical environments.]]>
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