# Energy Efficient Dynamic Symmetric Key Based Protocol for Secure Traffic Exchanges in Smart Homes
## 5 Performance Evaluation
### Experiments  
In this sub-section, the simulation results of the proposed protocol are presented. Owing to the wide acceptance of the network simulation (NS) tool, its latest version, NS3 (3.32), has been deployed. The host machine is an HP Elitebook Core i7 with 8 GB of RAM running on Ubuntu 20.04 LTS. Within the coordinate system, the TA is placed at the origin, while the remote users assume a random mobility model. The communication is over IEEE 802.11, operating at a frequency of 2.4 GHz, while the maximum range for the remote users is a square of 180 m, whose center is the TA. The speed of the remote users varies from 0 m/s to 5 m/s. On the other hand, the SHDs are randomly placed at locations between 25 m and 120 m away from the TA. The number of remote users is varied from 5 to 30, while the number of SHDs ranges from 5 to 25. The simulation is then executed for 10 min as the end-to-end latency and throughput are measured. The obtained end-to-end latency results are shown in Figure 8.  
Based on the graphs in Figure 8, the value of end-to-end latency increases with the number of SHDs. It is also evident that as the number of users increases, so does the end-to-end latency. This is explained by the processing delays at the TA as the number of authentication requests surges. The graphs are not entirely linear due to other transmission impairments, such as network congestion and packet losses that may trigger  
\begin{table}
\begin{tabular}{l l l l l} \hline \hline  & [39] & [40] & [47] & [56] & Proposed \\ \hline \multicolumn{5}{l}{Security feature} \\ \hline Backward key secrecy & - & - & - & - & \(\surd\) \\ \hline Forward key secrecy & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) \\ \hline Mutual Authentication & \(\surd\) & \(\surd\) & \(\times\) & \(\surd\) & \(\surd\) \\ \hline Secret key agreement & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) \\ \hline Device anonymity & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) \\ \hline Protection against: & & & & \\ \hline Packet replays & \(\times\) & \(\surd\) & \(\times\) & \(\surd\) & \(\surd\) \\ \hline Impersonation & \(\surd\) & \(\surd\) & \(\times\) & \(\surd\) & \(\surd\) \\ \hline Eavesdropping & - & & - & - & \(\surd\) \\ \hline Man-in-the-middle & - & & - & - & \(\surd\) \\ \hline Denial of service & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) \\ \hline Session hijacking & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) & \(\surd\) \\ \hline \hline \end{tabular} Legend, \(\surd\) Effective, \(\times\) Ineffective, - Not considered.  
\end{table}
Table 13: Security features comparisons.  
re-transmissions. Figure 9 shows the values for the measured throughput as the number of users and SHDs increments.  
It is evident from Figure 9 that throughput increases with both the number of users and the number of SHDs. This is attributed to the many bits sent and received across the network when users and devices increase. However, network congestions and packet drops within the network imply that the graphs are not always linear.