# SQRT: A Secure Querying Scheme of Routing Table Based on Oblivious Transfer
## 5 Experimental Results  
The hardware configuration of the directory server used in this experiment is Intel 4214R processor. The memory size is 256 GB. The network port is 25 Gbps. The software environment is CentOS Linux release 7.6. The hardware configuration of the user equipment is W-2145 8 core CPU, and the memory is 32 GB. In order to obtain the packets of routing querying requests and responses, we needed to create a packet capture module on the router in the local network. In order to mark the network traffic more efficiently, the method of capturing offline data needed to be improved. The experimental method in the paper was to run the routing table query operation according to the full buffer mode in the virtual machine, i.e., continuously generate the data packets of routing querying request and response in the anonymous networks. During the experimental test, the data packet was captured through the router in the local network with Wireshark, TCPDump, and other packet capture tools. Table 2 shows the security model and performance comparison results between the SQRT scheme proposed in this paper and the existing schemes. The security models are mainly divided into malicious model or semi-honest model, and the network performance includes the running time of the policy and the generated communication traffic. The BLAZE and TRIDENT schemes can realize multiplication under the malicious model; therefore, the communication traffic generated during the implementation of the above two schemes is relatively large. By comparison, the traffic generated by the TRIDENT scheme is lower than that of the BLAZE scheme. For the semi-honest model, the SQRT scheme proposed in this paper adopted the 3-out-of-10 oblivious transfer model. Compared with the onion routing and the galicia routing, the running time can be reduced by 16.9% and 34.5%, respectively, and the traffic can be reduced by 19.6% and 46.5%, respectively. Figure 5 shows the performance results of the SQRT scheme in terms of running time when \(N_{k}\) and \(\Delta\) take different values. It is worth noting that when analyzing the time overhead of cryptographic algorithms, we mainly focused on the public key cryptographic algorithms with a large amount of computation and longtime consumption, while ignoring the symmetric cryptographic algorithms with small overhead. Let \(N_{k}\) = 1,..., 10, \(\Delta\) = 1,..., and 10. With the increase in the values of \(N_{k}\) and \(\Delta\), the running time of the SQRT scheme increases accordingly, especially when \(N_{k}\geq 5\) and \(\Delta\geq 4\), the running time is higher than 500 ms. When \(N_{k}\) = 10, \(\Delta\) = 10, and the SQRT scheme adopts the more complex 10-out-of-20 oblivious transfer model, the running time reaches 714.5 ms. Therefore, the secure querying of the routing table can still be completed in less than 1s, and the user equipment can only obtain the information of 10 routing nodes fed back to the user equipment from the directory server, but not know the information of 10 additional routing nodes fed back \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**References**} & \multirow{2}{*}{**Schemes**} & \multirow{2}{*}{**Security Model**} & \multicolumn{2}{c}{**Performance Metrics**} \\ \cline{3-4}  & & & **Running** & **Communication** \\  & & & **Time/ms** & **Traffic/KB** \\ \hline
[4] & The Onion Routing & Semi-honest Model & 408.4 & 218.5 \\
[7] & The Galicia Routing & Semi-honest Model & 517.5 & 328.2 \\
[10] & BLAZE & Malicious Model & 419.0 & 426.8 \\
[11] & TRIDENT & Malicious Model & 498.2 & 379.1 \\ Our Paper & SQRT & Semi-honest Model & 339.2 & 175.6 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison of security model and performance among SQRT scheme and other existing schemes. by the directory server. On the other hand, the directory server knows neither the specific requirements of the routing nodes submitted by the user equipment, nor which 10 nodes the user equipment has selected among the 20 nodes fed back to the user equipment.