## 3 Results
### Exploring MCDM Approaches for Evaluating Cybersecurity Options in Smart Grids  
There are several other multi-criteria decision-making (MCDM) methods [94] that can be implemented to compare the results obtained from the analytical hierarchy process (AHP) and provide a broader perspective. Here are a few additional MCDM methods:  
* **Elimination Et Choix Traduisant la Realite (ELECTRE)**: ELECTRE is a family of MCDM methods that rank alternatives based on outranking relations. It considers multiple criteria and assesses the relative performance of alternatives through pairwise comparisons. The ELECTRE methods are particularly useful when dealing with imprecise or qualitative data.
* **VIseKrierijumska Optimizacija I Kompromisno Resenje (VIKOR)**: VIKOR is a multi-criteria decision-making method that combines compromise programming and outranking techniques. It determines a compromise solution by considering the maximum \"group utility\" and the minimum \"individual regret\". VIKOR can handle both quantitative and qualitative criteria.
* **Preference Ranking Organization METHod for Enrichment Evaluations II (PROMETHEE II)**: PROMETHEE II is an extension of the PROMETHEE method that incorporates preference functions and pairwise comparisons. It evaluates alternatives based on the net outranking flows and provides a ranking of alternatives. PROMETHEE II accounts for both positive and negative preference information.
* **Data Envelopment Analysis(DEA)**: DEA is a non-parametric method that evaluates the relative efficiency of alternatives. It considers multiple inputs and outputs to assess the efficiency of the alternatives and identify the most efficient ones. DEA can be particularly useful when there are limited or imprecise data available.
* **Grey Decision-Making Models**: grey decision-making models, such as grey relational analysis (GRA) and grey analytical network process (GANP), consider the uncertainty and limited information available in decision-making processes. These models can handle situations where the data are incomplete or imprecise, providing a different perspective on evaluating alternatives.  
* **Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)**: TOPSIS is a decision-making method that aims to find the alternative that is closest to the ideal solution and farthest from the negative ideal solution. It calculates the relative closeness of the alternatives based on their similarity to the positive ideal solution and their dissimilarity to the negative ideal solution. TOPSIS takes into account both positive and negative aspects of the criteria to determine the ranking of alternatives.
* **Weighted Sum Model (WSM)**: The weighted sum model (WSM) is a straightforward and widely used MCDM method. It involves assigning weights to criteria and aggregating the scores of the alternatives based on these weights. Each criterion is multiplied by its corresponding weight, and the results are summed to obtain a final score for each alternative. The alternative with the highest score is considered the best option. WSM is simple to implement and interpret, but it does not capture the interactions or trade-offs between criteria.  
Implementing these additional MCDM methods alongside AHP can provide a comparative analysis and enhance the robustness of the decision-making process in evaluating cybersecurity options for smart grids. It allows for a more comprehensive understanding of the results and aids in making informed decisions.