# A Hybrid Trust Model against Insider Packet Drop Attacks in Wireless Sensor Networks
## 5 Performance Evaluation
### Simulation Results
#### 5.2.3 Performance Comparison in a WSN with Temporal Burst Errors  
In this section, we examine how our hybrid trust model works in a WSN where packets can be dropped consecutively due to fading or temporal obstacles as well as insider packet drop attacks. We simulate this type of WSN in OPNET as follows. We deploy two blackhole attackers near the BS. In our simulation setup, 4% of packets are dropped naturally. We consider this natural packet drop rate as a normal error rate when there are no temporal errors in a WSN. Let the temporal error factor \(k\) be one at the normal error rate. To simulate temporal burst errors in a WSN, we temporarily increase the error rate by multiplying the normal error rate (=4%) by various \(k\) (up to 25) during a time duration (say, temporal error period). Then, during the period, packets are dropped with the increased error rate. We randomly choose 40% of nodes in which packets are dropped with various error rates during various error periods of 600, 1200, and 1800 s. The temporal error period starts randomly during the simulation. The higher the error rate and the longer the error period, the more packets are dropped during the error period; thus, the higher chance that packets are dropped consecutively. We explain the results by using the two performance metrics of false alarm rate and packet drop rate. First, our hybrid trust model does not generate a high false alarm rate, even in a WSN with various error rates and error periods. As shown in Table 5, in most setups (except when the error rate is extremely high), the false alarm rate of our hybrid trust model is the same as a normal error rate. This is because large consecutive drops are not likely to occur even when the temporal error rate is higher than the normal error rate. Meanwhile, when the error rate is set to be extremely high, such as 100%, the false alarm rate of our hybrid trust model is slightly increased to 0.11 because, in this setup, all packets are dropped consecutively. The false alarm rate of the beta trust model is increased to 0.02 when the temporal error period is 1800 s.  
Second, our hybrid trust model significantly reduces the packet drop rate of a routing, even in a WSN with various error rates and error periods. As shown in Table 5, when either the error rate or the error period grows, the packet drop rate of each routing also grows because packets are dropped more during the temporal error period. Figure 18 shows the detailed reasons for packet drops at various error rates when the error period is set to be 1200 s; in the figure, the number of packet drops due to attacks, temporal errors, and other network problems are depicted as attack (black), temp (gray), and others (white), respectively. When the pure GRP is used, most of packet drops occur due to the two undetected blackhole attackers. Meanwhile, since both trust-based routings can catch the attackers, they can dramatically reduce the packet drop rate compared to the pure GRP. In fact, our hybrid trust model avoids problematic nodes under the influence of temporal errors or collisions, as well as attackers, much faster than the beta trust model. Consequently, our hybrid trust model can further reduce packet drops.