A Trust-Based Secure Neuro Fuzzy Clustering Technique for Mobile Ad Hoc Networks

A MANET consists of a group mobile nodes. In MANET, scalability and mobility have greater influence on routing performance. The clustering technique plays vital role in enhancing the mechanism improving network lifetime large-scale like MANET. process will degrade performance if malicious node is chosen as Cluster Leader (CL). Thus, secure very challenging task. To overcome this problem, following key factors Trust Value (TV), Residual Energy Level (REL), Mobility (M) are used decision-making parameters to elect work, we proposed soft computing-based neuro-fuzzy model, ANFIS-based Energy-Efficient Secure Clustering Model (ANFIS-EESC), with primary objective forming energy-aware stable trust-based Moreover, two working novel algorithms: Weight-Based Estimation (WBTE) algorithm Fuzzy-Based (FBC) algorithm. WBTE measure trustworthiness nodes mitigate fuzzy logic-based cluster formation our each non-CL system applies density CL for using Mamdani Fuzzy Inference system, makes decision join member that holds maximum value. Simulation results show work enhances by electing more trust-aware leader We compare such packet delivery rate, energy consumption, detection reaffiliation, existing Weighted Algorithm (WCA). 39% ANFIS-EESC model than other WCA. shows an enhancement 22% 32% ratio throughput. From above analysis, it has been proved gives better terms reliability stability when compared