## 5 Evaluation  
In this section, we evaluate the performance of DAS scheduling, STD algorithm and CT algorithm through simulations on the simulator [27]. The experiments are conducted on a PC with an Intel Core i5-4210U(2.40 GHz) CPU and 8 GB memory running Ubuntu operating system and the Eclipse IDE. The sensor nodes are uniformly deployed in a rectangle monitor area. The size of this area is \(2000\times 2000\)\(m^{2}\). The experiment evaluates the security performance of the algorithm by testing the protection success rate (SR) value of the source node under different parameter settings. \(SR=\frac{ST}{NE}\times 100\%\), where \(ST\) is the number of times of security, which means the number of times the attacker actually captures time is greater than the expected capture time in the experiment, and \(NE\) is the number of experiments, that is, the total number of algorithm tests. According to Section 3.2, \(T_{S}=E\  
Table 2 and Figure 4 shows the performance of STD, DAS, and CT under different attack ranges. As can be seen from the experimental results, in most cases, both STD algorithm and CT algorithm interfere with the listening and tracking behavior of attackers, while the normal DAS scheduler has no impact on them. The STD algorithm is vulnerable to the impact of the size of the attacker's attack range, which makes the privacy protection effect of the algorithm fluctuate. In contrast, the privacy protection effect of the CT algorithm is relatively stable, and the success rate of protection is increased by 20%\(\sim\)50% compared with the STD algorithm. Figure 5 shows the performance of STD, DAS, and CT under different number of nodes. As the number of nodes increases, the number of hops the attacker can trace back to find the source node increases, so we can see from the figure that the success rate of protection increases as the number of nodes increases. Figure 6 shows the performance of CT under a different trap radius. From the figure we can see that when the trap radius is less than 500 m, the attacker is more likely to detect the node on the trap, and the protection success rate increases as the trap radius increases. However, when the trap radius is larger than 500 m, the probability that the attacker and the source node fall into the trap at the same time increases, which causes the trap to be ineffective, and the protection success rate is reduced. Figure 7 shows the latency of STD, DAS, and CT under 20 different networks. We can know from the experimental results that DAS algorithm has the minimum latency. The CT and STD algorithms adjust the slot values of some nodes to construct trap, so the TDMA slot value of the network increases. In order to improve the security of the algorithm, a slight network latency is allowed within our acceptable range. Figure 8 shows the latency of STD, DAS and CT under different number of nodes. The maximum value of TDMA slot increases as the number of nodes increases, so we can see from the figure that the latency increases as the number of nodes increases. Figure 9 shows that the latency increases as the radius of the trap increases. \begin{table}
\begin{tabular}{c c} \hline
**Parameter Name** & **Parameter Value** \\ \hline \multicolumn{2}{c}{Network parameters} \\ \hline Network coverage area & \(2000\times 2000\) m\({}^{2}\) \\ Network node distribution & Uniform grid distribution \\ Node communication radius & 50 m \\ Number of nodes & 1600 \\ Number of experiments NE & 1000 \\ Attack Range & 50 \\ \hline \multicolumn{2}{c}{STD algorithm parameters} \\ \hline Search length d & 3 \\ False path length lenD & 20 \\ \hline \multicolumn{2}{c}{CT algorithm parameters} \\ \hline Large circle radius of the ring & 400 m \\ Small circle radius of the ring & 300 m \\ \hline \end{tabular}
\end{table} 
Table 1: Experimental parameters. \begin{table}