Quantum networks are essential for secure quantum communication and distributed quantum computing. However, their performance is highly vulnerable to targeted attacks that disrupt entanglement distribution, leading to significant network degradation. To address this challenge, we propose two heuristic routing algorithms Quantum Entanglement Distribution Algorithm 1 (QEDA1) and Quantum Entanglement Distribution Algorithm 2 (QEDA2) that minimize loss of fidelity by reducing the number of intermediate nodes while optimizing entanglement swapping and purification strategies. In QEDA1 we only applied purification as a recovery mechanism, while in QEDA2 we utilized a purification-rerouting approach. Furthermore, unlike previous studies, which relied primarily on idealized or small-scale topologies, we evaluated our approach on a real-world network topology (Surfnet), analyzing throughput variations under both normal conditions and targeted attacks. Furthermore, we compare the performance of the algorithm in memory-assisted and memoryless quantum networks, demonstrating the impact of quantum memory on network resilience. In addition, we introduce an attack model based on centrality-driven node failures and propose a recovery mechanism that integrates rerouting and entanglement purification to mitigate the effects of targeted attacks. Our results indicate that QEDA2 is more effective in mitigating the effect of attacks on throughput. Moreover, our findings highlight the trade-offs between network robustness, resource allocation, and fidelity constraints, providing valuable insights for the design of resilient large-scale quantum networks.