## 3 Results and Discussion
In this paper, the specialized tools MCDA Methods Selection Software (MCDA-MSS) [37] and Weighting Methods Selection Software (WEMSS) [38] were used to select the optimal methods of multi-criteria decision making. The process of working with the MCDA-MSS program was as follows. In order to determine which method or, possibly, several methods of multi-criteria decision making were suitable for the problem under consideration, it was necessary to answer a series of questions consisting of four groups. Each question had several answer options, including the answer \"I don't know\" (i.e., it is possible that the user may not know how to answer the question at the time of working with the tool). The questions and answers had descriptions explaining their meaning. When choosing answers to some questions or to all questions, a list of methods that the system recommended for the problem under consideration automatically appeared. Moreover, for each method, a description was given with a list of answers to questions corresponding to this method. The selected answers would be highlighted in bold. The first group of questions was called \"Problem Formulation\". The answers to these helped determine what type the problem under consideration belonged to and what structure it had. The second group of questions is called \"Preference Model\". These helped to find out what type of model should be applied to the problem under consideration. The third group of questions was called \"Preference Elicitation\". The questions of this group were designed to determine the type, modality, and frequency \begin{table}
\begin{tabular}{c c c} \hline \hline
**Criteria** & **Qualitative Measures** & **Quantitative Measures** \\ \hline C\_3—finalization & Probabilistic/Deterministic & 1/9 \\ C\_8—power consumption & Low/Medium/High & 1/5/9 \\ C\_9—hardware dependency & No/Yes & 1/9 \\ C\_12—51% attack & Vulnerable/Safe & 1/9 \\ C\_13—double spending & Vulnerable/Difficult/Safe & 1/5/9 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Qualitative criteria. of the model preferences. The last group of questions was called \"Using the Preference Relationship Given by the Preference Model\". It defined the strategy used to obtain and improve decision recommendations. Thus, as a result of receiving the answers to the questions of the above groups, the user could receive a list of recommended methods. However, there may be a case when the list is empty. Currently, the MCDA-MSS database contains more than 205 multi-criteria decision making methods and 156 key decision characteristics. MCDA-MSS can be useful for researchers and practitioners working in the field of multi-criteria decision making [39; 40; 41]. When working with the WEMSS system, the user similarly answered a number of interactive questions grouped into three sections. As a result of receiving answers, the user received a list of recommended weighting methods. Currently, the WEMSS database contains 35 weighting methods and 50 key decision characteristics. In the process of working with the MCDA-MSS tool, answering the questions proposed by the system, the main characteristics that the selected method of multi-criteria decision making should satisfy were determined. As a result, the system proposed the following options: TOPSIS, fuzzy TOPSIS, TOPSIS interval, TOPSIS interval and fuzzy, VIKOR, and fuzzy VIKOR. The nature of the input data in the considered multi-criteria decision-making problem affects the final choice of the methods proposed by the MCDA-MSS system. If the available input data were clear and deterministic, and it was necessary to find an alternative closest to the ideal alternative, then the TOPSIS method could be selected. If the input data were clear and deterministic, and it was important to take into account the trade-off between the criteria, then the VIKOR method could be selected. If the input data were fuzzy, and strict ordering of the criteria was required, then the fuzzy TOPSIS method could be selected.