# Multilevel Privacy Assurance Evaluation of Healthcare Metadata
## 3 Multilevel Privacy Assurance Evaluation: Results and Evaluation
### At Third-Party Data Processing Level
\begin{table}
\begin{tabular}{c c c c c} \hline \multicolumn{2}{c}{**Quality Indicators**} & \multicolumn{2}{c}{**Precision**} \\ \hline \multicolumn{2}{c}{**Respective Metric Names**} & **Precision** & **Backward** & **Balanced** \\ \hline \multirow{2}{*}{\
\begin{tabular}{c} Test-Model \\ (Sepsis) \\ \end{tabular} } & Raw Event-log & \multirow{2}{*}{0.5353} & \multirow{2}{*}{0.3989} & \multirow{2}{*}{0.4671} \\  & \(\mathit{TM}_{1}\) (20 \% noise) & & & \\  & \(\mathit{TM}_{2}\) (add chaotic-events) & & & \\  & \(\mathit{TM}_{3}\) (add frequent chaotic-events) & & & \\  & \(\mathit{TM}_{4}\) (add infrequent chaotic-events) & & & \\  & \(\mathit{TM}_{5}\) (swap trace-events) & & & \\  & \(\mathit{TM}_{6}\) (low frequency filtered-out) & & & \\  & \(\mathit{TM}_{7}\) (high frequency filtered-out) & & & \\  & \(\mathit{TM}_{7}\) (high frequency filtered-out) & & & \\ \hline \multirow{2}{*}{
\begin{tabular}{c} Test-Model \\ (Hospital billing) \\ \end{tabular} } & Raw Event-log & \multirow{2}{*}{0.5346} & \multirow{2}{*}{0.5844} & \multirow{2}{*}{0.6268} \\  & \(\mathit{TM}_{8}\) (Anonymized Event-log) & & & \\  & \(\mathit{TM}_{9}\) (Obfuscate lit-event-atri-values) & & & \\  & \(\mathit{TM}_{10}\) (Obfuscate & & & \\  & \(\mathit{ext}\)-atri-name) & & & \\  & \(\mathit{TM}_{11}\) (Add/change concept) & & & \\  & \(\mathit{TM}_{6}\) (low frequency filtered-out) & & & \\  & \(\mathit{TM}_{12}\) (reversed log) & & & \\ \hline \end{tabular}
\end{table} 
Table 2: ProM experiments results for the 2 test models and 12 training models using noise-adding plugins (Precision). \begin{table}
\begin{tabular}{c c c c c} \hline \hline
\begin{tabular}{c} Addition of k \\ frequent \\ randomly \\ positioned \\ activities \\ \end{tabular} & \(\times\) & ✓ \\ \hline \hline \end{tabular}
\end{table} 
Table 4: 12 noise-adding plugins, their noise addition types, their and utility vis-a-vis privacy levels. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Quality Indicators** & \multicolumn{3}{c}{**Complexity**} \\ \hline \multicolumn{3}{c}{**Respective Metric Names**} & **ECyM** & **ECaM** \\ \hline Test-Model (Sepsis) & Raw Event-log Model & 295 & 24 \\ \hline \multirow{6}{*}{3 rd} & \(TM_{1}\) (20 \% noise) & 825 & 24 \\  & \(TM_{2}\) (add chaotic-events) & 319 & 25 \\  & \(TM_{3}\) (add frequent chaotic-events) & 714 & 28 \\  & \(TM_{4}\) (add infrequent chaotic-events) & 307 & 25 \\  & \(TM_{5}\) (swap trace-events) & 3472 & 28 \\  & \(TM_{6}\) (low frequency filtered-out) & 204 & 21 \\  & \(TM_{7}\) (high frequency filtered-out) & 295 & 24 \\ \hline \multirow{2}{*}{Test-Model (Hospital billing)} & \multirow{2}{*}{Raw Event-log Model} & \multirow{2}{*}{1946.0} & \multirow{2}{*}{35.0} \\  & & \(TM_{1}\) (20 \% noise) & 10011.0 & 37.0 \\  & \(TM_{8}\) (Anonymized Event-log) & 897 & 34 \\  & \(TM_{9}\) (Obfuscate lit-event-attri-values) & 897 & 34 \\  & \(TM_{10}\) (Obfuscate event-attri-name) & 984.0 & 34.0 \\  & \(TM_{11}\) (Add/change concept) & 454 & 33 \\  & \(TM_{6}\) (low frequency filtered-out) & 16 & 12 \\  & \(TM_{12}\) (reversed log) & 47 & 25 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: ProM experiments results for the 2 test models and 12 training models using noise-adding plugins (Complexity).