Optimizing Security Measures in Decentralized Mobile Networks with Neutrosophic Fuzzy Topology and PKI

This study proposes a method to improve the security of decentralized mobile networks using Neutrosophic Fuzzy Local Function Algorithms D*, B*, and A* to optimize the decision variables (C, B, A), which are associated with different security measures. The three measures of confidence, integrity, and specificity (τ,1, and
$v$
)) are used to evaluate the effectiveness of the proposed method. The study presents the optimal values for the three different resolutions (C, B, A) for each condition, as well as the associated τ, i, and
$v$
. The results show that the proposed method can effectively improve the security of decentralized mobile networks. The T, i, and v values increase with the increase in the number of nodes, indicating that the proposed method is adaptable to larger-sized networks. Additionally, the optimal values for the three different resolutions increase with the increase in the number of nodes, indicating that the method can effectively improve the T, i, and i. Overall, the study demonstrates the effectiveness of the proposed method in improving the security of decentralized mobile networks. By combining neutrosophic fuzzy topology and PKI and optimizing decision variables using Neutrosophic Fuzzy Local Function algorithms, the proposed method can effectively handle uncertainty and indeterminacy in data while providing authentication and encryption.