## 6 Experimental Results
### Comparative Analysis
#### 6.2.4 Analysis of Attack Mitigation/Prevention Rate  
The attack mitigation/prevention rate is defined as the amount of attack mitigated/prevented by the model with the number of security threats. Mathematically, the attack mitigation/prevention rate can be defined as:  
\[\text{Att}^{\text{pre/mit}}=\frac{\text{Tot}^{\text{Attpre/mit}}}{\sum\text{ cyber threats}}\times 100 \tag{42}\]  
where \(\text{Tot}^{\text{Attpre/mit}}\) is the amount of attack detected/mitigated and \(\sum\text{cyber}\) threats is the summation of cyber threats. Figure 9 represents the comparison of attack mitigation/prevention rate with respect to the number of SDWSN nodes among the proposed MTS-SDWSN and existing SEMRP-WSN and EDASS works, respectively. From the graphical inference, it is revealed that the proposed work has a higher attack mitigation/prevention rate than the existing works. The reason for such a higher mitigation/prevention rate by the proposed work is that we perform MTD operation in our work. More clearly, the MTD operations by the reconnaissance agents in both the infrastructure and edge-assisted switch layer, respectively, in terms of route switching and active switch handling. The adopting of MTD operations in the proposed environment is more precisely to resist the reconnaissance attacks in the SDWSN environment. On the other hand, the existing SEMRP-WSN and EDASS works did not consider the security measures in their network leads to higher possibility of network entities to be vulnerable to cyberattacks, thereby decreasing the attack mitigation/prevention rate. The quantitative analysis from the graph shows that the proposed MTS-SDWSN has a higher attack mitigation and prevention rate of 97% when the SDWSN nodes reach 100, whereas for the same SDWSN nodes the attack mitigation and prevention rate of SEMRP-WSN and EDASS gains with 82% and 79%, respectively, which is 15-18% less than our proposed model. Figure 8: Number of SDWSN nodes vs. end-to-end delay. In the connectivity-aware network construction stage, the entities involved in the infrastructure layer are properly placed in 2D hexagonal grids to overcome the connectivity and coverage hole issues. In the density-based clustering stage, the SDWSN nodes are clustered using the DWTMB algorithm based on density and mobility. From the clustered nodes, the optimal CL is selected using high residual energy, less mobility, less distance from the local gateway, and high trust score. In addition, we have also maintained the cluster-by-cluster merging and splitting methods, respectively. In the multi-tier federated scheduling stage, the CMs-CLs, CLs-LBSs, and LBSs-SN are scheduled in three tiers using the NCFT algorithm with specific scheduling metrics. By performing multi-tier scheduling, the problem of complexity and collisions gets reduced. In MTD-based secure two-way routing, the SORP is proposed to select and rank the best routes using the AFT and MCDM algorithms, respectively. Furthermore, the trust evaluation and MTD methods are introduced in the proposed routing protocol for reduce cyber threats. The NS-3.26 is a simulation tool used by the proposed work to implement the proposed model in which the performance is analyzed with four major performance metrics such as energy consumption (J), PDR (%), E2E(s), and attack mitigation/prevention rate (%) among the proposed and existing works. The simulation results reveal that the existing model underperforms the proposed work. In the future, more works and investigations will be conducted on multitier scheduling in the SDWSN environment using different performance metrics such as temperature, electromagnetic noise, radiation, and weather conditions. Conceptualization, A.M.A.A. and (H.H. ); data curation, A.A.M.S. and S.S.S. ; formal analysis, (H.H. ), S.S.S. and A.A.M.S. ; investigation, A.M.A.A., (H.H.) and S.S.S. ; methodology, A.M.A.A. and S.S.S. ; resources, A.A.M.S. ; software, (H.H. ); supervision, A.M.A.A. ; validation, A.M.A.A. and S.S.S. ; visualization, A.A.M.S. ; writing--original draft, A.M.A.A., (H.H.