MANETs are more exposed to intrusion vulnerabilities as compared to wired networks depending on factors such as dynamic network architecture, mobility of nodes, a compromised operating environment, and various additional other elements. MANET can be safeguarded via data encryption, reliable routing algorithms, intrusion detection systems (IDS), or a mixture of these technologies. Although there are many different routing protocols readily available that enhance network acceleration, only a few of them target security-related issues. This research proposes an I-AODV routing protocol for routing the data that implementing K-means. The whale optimization approach with artificial neural network has been employed in preventing launched attacks called “Hybrid Secure Clustering Multi-Threat Prevention and Mitigation technique (HSCMM)”. This approach can identify threat such as black holes, flooding, and selective packet dropping. The Proposed method generates Throughput 12730, E2E delay 0.018 to 0.5, packet dropping rate 0% to 3%, and PDR 97% to 100%.