# Mitigating DDoS Attacks in LEO Satellite Networks Through Bottleneck Minimize Routing
## 5 Simulation and Result
### Result  
As illustrated in Figure 4, the CDF of attacker costs demonstrates that our K-Bottleneck Minimize routing algorithm substantially increases adversarial resource requirements compared to K-SP and K-DG satellite routing schemes. The gradual ascent of the curve in low-cost regions suggests limited initial impact on path selection strategies, while its flattened progression in high-cost intervals reveals progressive cost escalation during sustained attacks, achieving our design objective. This cost inflation stems from attackers being compelled to select low-utilization paths rather than exploiting bottleneck links with concentrated traffic flows, thereby increasing total required attack traffic volume.  
Figure 5 presents mean and median attack costs across compared algorithms. In Figure 5a, our proposed method achieves the highest average cost among all strategies, demonstrating improvements of 13.1% over K-SP and 21.6% over K-DG. In Figure 5b, it also attains the highest median cost, showing gains of 16.6% and 20.3% compared to K-SP and K-DG, respectively. These statistically significant increments validate the algorithm's effectiveness in elevating attack barriers, particularly crucial for large-scale LSN deployments. The elevated cost requirements indicate that potential attackers would need to coordinate botnets of a considerably larger scale to successfully penetrate such defenses. This inherent advantage not only enhances the security of LSN infrastructures but also creates substantial economic and operational barriers for would-be attackers, as the resource requirements for mounting effective attacks become prohibitively high.  
Figure 4: CDF of adversary’s cost launching attack on LSN.  
The detectability analysis in Figure 6 reveals that K-Bottleneck Minimize exhibits the highest MaxUp values among compared schemes, indicating greater susceptibility to satellite operator detection. This trend correlates with the cost CDF pattern, as achieving equivalent congestion effects under K-Bottleneck Minimize necessitates larger traffic volumes, thereby amplifying observable anomalies for network monitoring systems.  
The experimental evaluation reveals the remarkable effectiveness of the K-Bottleneck Minimize strategy in defending against DDoS attacks. Figure 7 illustrates the average and median attack MaxUp values across the algorithms under comparison. As shown in Figure 7a, K-Bottleneck Minimize achieves an average MaxUp value of 0.251, which is 48.5% higher than the 0.169 average recorded by K-SP. This performance advantage extends to comparisons with K-DG, exceeding the K-DG average of 0.192 by 30.7%. In Figure 7b, when examining the median values, K-Bottleneck Minimize maintains its superiority with a 0.205 value, representing a 45.4% improvement over K-SP 0.141 median. The comparison shows an even more striking difference, where outperforms K-DG 0.131 median by 56.5%.  
Figure 5: Attack cost of different strategy. (**a**) Average attack cost for each strategy; (**b**) Median attack cost for each strategy.  
Figure 6: CDF of adversary MaxUp launching attack on LSN.  
These substantial improvements in MaxUp metrics directly translate to enhanced network security. The elevated thresholds force attackers to generate traffic surges of significantly greater magnitude, increasing the likelihood of anomalous patterns being detected. As a result, the deployment of K-Bottleneck Minimize not only imposes prohibitive resource demands on adversaries but also enables network administrators to more readily identify sudden traffic anomalies. This facilitates earlier detection of potential attacks and allows for more effective and timely threat mitigation.