# A Privacy-Preserving Record Linkage Method Based on Secret Sharing and Blockchain
## 4 Methods
### Output and Audit Module
#### 4.4.4 Record Keeping and Provenance
The recall variation with the number of participants in the three perturbed datasets is shown in Figure 8.

The specific recall values for the three perturbed datasets as the number of participants varies are shown in Table 4.

Under varying numbers of participants and perturbation levels, the Yao method achieves the highest F-score and strong anti-interference capability, benefiting from improvements in its linkage approach. Our proposed method and the Vatsalan method, however, are primarily influenced by the Bloom filter and simi

Figure 8: The recall variation with the number of participants in the three perturbed datasets. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Method** & **Participants = 3** & **Participants = 5** & **Participants = 7** & **Participants = 9** \\ \hline \multirow{3}{*}{SSB-PPRL} & 0.78 (Mod-1) & 0.74 (Mod-1) & 0.68 (Mod-1) & 0.61 (Mod-1) \\  & 0.73 (Mod-2) & 0.68 (Mod-2) & 0.62 (Mod-2) & 0.56 (Mod-2) \\  & 0.67 (Mod-3) & 0.61 (Mod-3) & 0.57 (Mod-3) & 0.5 (Mod-3) \\ \hline \multirow{3}{*}{[PERSON]} & 0.71 (Mod-1) & 0.67 (Mod-1) & 0.62 (Mod-1) & 0.56 (Mod-1) \\  & 0.65 (Mod-2) & 0.62 (Mod-2) & 0.56 (Mod-2) & 0.51 (Mod-2) \\  & 0.58 (Mod-3) & 0.56 (Mod-3) & 0.49 (Mod-3) & 0.45 (Mod-3) \\ \hline \multirow{3}{*}{Yao} & 0.88 (Mod-1) & 0.84 (Mod-1) & 0.79 (Mod-1) & 0.74 (Mod-1) \\  & 0.82 (Mod-2) & 0.78 (Mod-2) & 0.73 (Mod-2) & 0.69 (Mod-2) \\  & 0.76 (Mod-3) & 0.72 (Mod-3) & 0.67 (Mod-3) & 0.64 (Mod-3) \\ \hline \multirow{3}{*}{Vatsalan} & 0.76 (Mod-1) & 0.73 (Mod-1) & 0.67 (Mod-1) & 0.62 (Mod-1) \\  & 0.71 (Mod-2) & 0.68 (Mod-2) & 0.62 (Mod-2) & 0.56 (Mod-2) \\ \cline{1-1}  & 0.65 (Mod-3) & 0.62 (Mod-3) & 0.55 (Mod-3) & 0.5 (Mod-3) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Precision values for three perturbed datasets changing with participant numbers. Figure 7: The precision variation with the number of participants in the three perturbed datasets. terms of linkage quality. The Han method improves data structure for better efficiency but experiences a slight decline in linkage quality. The F-score variation with the number of participants in the three perturbed datasets is shown in Figure 9.

The specific F-score values for the three perturbed datasets as the number of participants varies are shown in Table 5. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Method** & **Participants = 3** & **Participants = 5** & **Participants = 7** & **Participants = 9** \\ \hline \multirow{3}{*}{SSB-PPRL} & 0.76 (Mod-1) & 0.72 (Mod-1) & 0.66 (Mod-1) & 0.59 (Mod-1) \\  & 0.71 (Mod-2) & 0.66 (Mod-2) & 0.61 (Mod-2) & 0.53 (Mod-2) \\  & 0.65 (Mod-3) & 0.59 (Mod-3) & 0.56 (Mod-3) & 0.47 (Mod-3) \\ \hline \multirow{3}{*}{Han} & 0.69 (Mod-1) & 0.65 (Mod-1) & 0.6 (Mod-1) & 0.54 (Mod-1) \\  & 0.63 (Mod-2) & 0.6 (Mod-2) & 0.54 (Mod-2) & 0.49 (Mod-2) \\  & 0.57 (Mod-3) & 0.55 (Mod-3) & 0.47 (Mod-3) & 0.43 (Mod-3) \\ \hline \multirow{3}{*}{Yao} & 0.86 (Mod-1) & 0.83 (Mod-1) & 0.78 (Mod-1) & 0.73 (Mod-1) \\  & 0.8 (Mod-2) & 0.77 (Mod-2) & 0.72 (Mod-2) & 0.68 (Mod-2) \\  & 0.73 (Mod-3) & 0.71 (Mod-3) & 0.66 (Mod-3) & 0.63 (Mod-3) \\ \hline \multirow{3}{*}{Vatsalan} & 0.75 (Mod-1) & 0.73 (Mod-1) & 0.65 (Mod-1) & 0.6 (Mod-1) \\  & 0.7 (Mod-2) & 0.67 (Mod-2) & 0.6 (Mod-2) & 0.54 (Mod-2) \\ \cline{1-1}  & 0.65 (Mod-3) & 0.61 (Mod-3) & 0.54 (Mod-3) & 0.47 (Mod-3) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Recalling values for three perturbed datasets changing with participant numbers.