To improve the performance of the wireless network, different types of topologies were introduced like start, ring, bus, mesh and dynamic topology. However, providing the security is the very difficult because of the unique environment. But, affording the security is most required task to avoid less data transmission and high data loss. Hence, a novel Chimp based Associativity routing (CbAR) was proposed for predicting and neglecting the malicious events in the mesh network. The dataset that has utilized for the performance testing process is CICIDS database. Besides, the robustness of the proposed model is validated by launching the Denial of Service (DoS) attack in the mesh topology. Moreover, the planned model is tested in the python environment. Finally, the communication and attack prediction parameters like tthroughput, accuracy, delay, transmission time, packet drop and data transfer rate have been validated and compared with other existing models. In that, the presented model has gained high accuracy, throughput and data transfer rate. Also, it has minimized delay and data flow rate.
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