## 4 Simulation Results
Figure 4: _Cont._  
Figure 3: Filtering performance analysis. Figure 5 shows that, as long as the value of \(T_{f}\) is same for all three schemes, i.e., PVFS, FASIN, and our proposed method, the early filtering of fabricated reports is better in our proposed scheme as the distance between the e-CH and the BS increases. It is extremely desirable to relieve the nodes closer to the BS of the task of verification because they contain more verification keys and must perform verification more often. All those reports for which \(T_{t}\) reaches its threshold value are marked safe and are not verified any further, which eases the task of the verification nodes located farther from the e-CH. Figure 6 shows the average energy consumed in forwarding a false report before it is filtered by an intermediate verification node. Initially, when there is no false data insertion in the network and the sensor nodes are fully charged, the proposed scheme chooses the shortest path for data delivery like in PVFS and FASIN. However, the false data rate increases, and the energy of the intermediate nodes decreases with the passage of time. In the proposed scheme, the e-CH makes fuzzy inferencing about the path selection and chooses the best path given the current insertion rate of false data and the status of the energy of the intermediate paths. Whereas, FASIN and FVPS switch to the next shortest path for data delivery only after a node failure occurs on the first shortest path. Whenever FASIN switches to the available next shortest path, the verification nodes on that path are sparsely located due to initial  
Figure 4: Fabricated packets dropped en-route. (**a**) Probabilistic voting-based filtering scheme (PVFS); (**b**) Fuzzy adaptive path selection without FASIN; (**c**) Fuzzy adaptive selection of verification nods (FASIN); (**d**) Proposed method. Figure 5: Fabricated report filtering performance. probabilistic selection of the verification nodes. Therefore, false reports travel more hops than in the proposed method and consume more energy until FASIN improves the proximity of the verification node to the e-CH. In PVFS, verification nodes are probabilistically chosen only once and they remain fixed. The bend in the curve for PVFS in Figure 6 is due to the fact that verification nodes that are near the source cluster have a higher probability of being chosen as verification nodes on a longer path than on the shortest path as provided by Equation (2). Intermediate nodes may ultimately die earlier than other nodes because they are constantly involved in data forwarding as extra energy is expended during data receiving, verifying and forwarding. Consequently, loss of information inevitably occurs due to the fact that information generated by event reporting clusters cannot reach the BS because one or more of the intermediate nodes on the data routing paths have been depleted and have gone dead. Figure 7a,b show information delivery and loss analysis of PVFS, FASIN, and the proposed method. The proposed method outperforms PVFS as well as FASIN with the improved information delivery and reduced information loss. It is very obvious from Figure 7a,b that our proposed method helps to prevent energy depletion in the intermediate nodes, hence the network operational time is increased. Figure 6: Average energy consumption per false report. Figure 7: Information delivery and loss analysis. (**a**) Attack ratio = 60%; (**b**) Number of reports generated = 400.