## 5 Experiment and Result  
In this section, we describe the experiments and outcomes. This includes evaluation metrics and the compared methods. The results of the experiments are then presented, along with the analysis drawn from them.  
Result and Analysis  
The result from Table 1 clearly shows the various times to match a fingerprint from the sensor database. This reflects the time-based efficiency of the system. It was discovered that it took user 1 about 3 s to match, then validated by the AccesSensor. Conversely, it took User 1 approximately 4 s to be matched and validated by the DPSensor [26]. However, this time difference tends to be equal, when User 3 and User 4 fingerprints are validated at (10 s, 10.1 s) and (15 s, 15.2 s), respectively, as seen in Figure 8. This indicates that our method efficiently uses less time to execute its task.  
Furthermore, the outcome of the masking process as a privacy preservation measure by the AccesSensor, in contrast to the noise addition mechanism of the DPSensor is depicted in Figure 9. The validated finger ID of User 2 took our method, 9 s to be masked while the noise addition method of the DPSensor took 11.5 s to complete this privacy preservation process. Thus, this shows that our masking method is faster and more efficient in user validation than the compared method.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**User**} & \multicolumn{2}{c}{**AccesSensor**} & \multicolumn{2}{c}{**DPSensor**} \\ \cline{2-5}  & **Time to Match (s)** & **Time to Mask (s)** & **Time to Match (s)** & **Time to AddNoise (s)** \\ \hline User 1 & 3 & 4 & 4 & 6 \\ User 2 & 7 & 9 & 7.2 & 11.5 \\ User 3 & 10 & 15 & 10.1 & 16.7 \\ User 4 & 15 & 19 & 15.2 & 19.7 \\ User 5 & 18 & 22 & 18.4 & 23.6 \\ User 6 & 21 & 26 & 22 & 22.6 \\ User 7 & 27 & 33 & 27.8 & 27.9 \\ User 8 & 32 & 38 & 32.9 & 39 \\ User 9 & 37 & 41 & 38 & 43 \\ User 10 & 38 & 41.6 & 38.5 & 43.7 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison of Time-based Efficiency.  
Figure 8: Time-based Efficiency of Sensors.  
In terms of bandwidth utilization, edge network devices as well as IoT devices are displayed in Table 2. The AccesSensor matched and granted access to users 1-4, utilizing lower bandwidths of 0.12, 0.5, 0.9, and 3.087 Mbps, respectively, to obfuscate the validated fingerprints. Conversely, the DPSensor utilized a higher bandwidth of 0.15, 0.8, 3.4, and 3.8, respectively, to match, validate and carry out noise addition as a privacy measure. For users 5 to 10, the result is different as it requires more for noise addition. This clearly shows the AccesSesor's edge over the DPSensor as represented in Figure 10.  
\begin{table}
\begin{tabular}{l c c} \hline \hline
**User** & **AccesSensor—BW** & **DPSensor—BW** \\ \hline User 1 & 0.15 & 0.12 \\ User 2 & 0.8 & 0.5 \\ User 3 & 3.4 & 0.9 \\ User 4 & 3.8 & 3.087 \\ User 5 & 3.95 & 3.669 \\ User 6 & 3.99 & 3.816 \\ User 7 & 4 & 3.879 \\ User 8 & 3.991 & 3.983 \\ User 9 & 4.2 & 4.023 \\ User 10 & 4.3 & 4.086 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Comparison of AccesSensor and DPSensor Bandwidth (BW).  
Figure 10: Bandwidth Utilization for User Validation.  
Figure 9: Efficiency of Privacy Method of Sensors.