## 5 Platform Testing and Validation
### Platform Validation
#### 5.4.2 End-User's Feedback  
Based on the defined validation criteria, Table 5 summarizes the main assessment results obtained out of the quality parameters evaluation performed over the proposed platform [43].  
As can be seen from the previous table, the overall quality assessment of the proposed platform is good or very good. it is important to note that besides Mekorot, two other water utilities (i.e., Berlin Wasserbetriebe ([[https://www.bwb.de/de/index.php](https://www.bwb.de/de/index.php)]([https://www.bwb.de/de/index.php](https://www.bwb.de/de/index.php)), accessed on 5 June 2021), Oslo Water and Sewerage Works ([[https://www.oslo.kommune.no/politics-and-administration/statistics/environment-status/water-and-waterways/#gref](https://www.oslo.kommune.no/politics-and-administration/statistics/environment-status/water-and-waterways/#gref)]([https://www.oslo.kommune.no/politics-and-administration/statistics/environment-status/water-and-waterways/#gref](https://www.oslo.kommune.no/politics-and-administration/statistics/environment-status/water-and-waterways/#gref)), accessed  
\begin{table}
\begin{tabular}{l c c c c c c} \hline \hline
**Parameter** & **1** & **2** & **3** & **4** & **5** & **Comments** \\ \hline \hline \begin{tabular}{l} Ease of installation \\ Facilitation of user \\ learning \\ Data requirements \\ Support \\ Integrity \\ \end{tabular} & & & & & & & No major issues identified during installation \\ \begin{tabular}{l} Facilitation of user \\ learning \\ Data requirements \\ \end{tabular} & & & & & & Appropriate user guidelines to learn and demonstrate tools/platform capabilities \\ \begin{tabular}{l} Output \\ Integrity \\ \end{tabular} & & & & & & Data anonymization is required prior testing \\ \begin{tabular}{l} Usability \\ \end{tabular} & & & & & & & & \\ \
\begin{tabular}{l} Usability \\ \end{tabular} & & & & & & & & \\
\begin{tabular}{l} Usefulness \\ \end{tabular} & & & & & & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 5: Quality Parameters Evaluation.  
on 5 June 2021)) have participated in the platform testing and validation by reflecting how useful the proposed solution is in their operational contexts in terms of (i) accuracy improvement (higher detection of physical/cyber-attacks and incidents); (ii) latency reduction; (iii) response time; (iv) preparedness improvement; (v) reduction of human exposure; and (vi) cost effectiveness. The end users, as tokens of expert judgment, can project and estimate the expected impact the platform will have to their line of work, as well as to the level of protection that can be achieved with the framework. This reflection on projected impact creates a surrogate validation scheme, based on expert end-user judgment, to measure the impact of the platform in the end-user domains.  
The following aspects have been considered during testing and validation of the proposed solution:  
* Anonymized data are used during the whole process.
* NTSA training dataset must include legitimate connections to develop the machine learning model of the network behavior for each water CI. The testing dataset must contain anomalous connections (e.g., attacks).
* Some of the platform tools (e.g., JDet, NTSA) can operate using physical deployment, others (e.g., XL-SIEM, RTAD) use a cloud-based deployment and others can use both.
* Devices from the end-user infrastructure can be physical, virtualized, or both.
* End users must define their own security policies and rules to detect attacks in their infrastructures.
* The platform is expected to perform the detection analysis in real time.