An Ensembled Optimization Algorithm for Secured and Energy Efficient Low Latency MANET with Intrusion Detection

The property of dynamic infrastructure that adjusts the network automatically and allows for faster deployment has made Mobile ad hoc networks (MANETs) extremely fitting for locations that don’t have support for radio communication due to disasters or other crises. Since the topology is dynamic, security is one of the major concerns in MANET which will be exposed for various attacks like eavesdropping, routing based attacks and modification of executables. Though MANET is vulnerable to these attacks, another major issue to be addressed is the attacks based on intrusion. The proposed model uses an Ensemble optimization algorithm that addresses the security issues in MANET by the effective usage of the Cluster Head and the intrusion detection is done by using fuzzy clustering and fuzzy Naïve Bayes models. The algorithms considered here are, Chimp Optimisation technique and Grasshopper Optimization methodology. Chimp Optimization technique selects cluster head that selects the optimized route for the dynamic performance of MANET. The optimal routes are chosen related to few parameters are conformity, power, certainty, and bandwidth. Grasshopper Optimization Algorithm is used to reduce the defects to obtain better global optimization ability. The implementation of the above techniques are measured by different assaults like flooding, blackhole, and selective packet drop and Ensembled optimization is found to perform well than the individual algorithms.