Clustering in wireless sensor networks (WSNs) offers numerous desirable properties, including load balancing, energy conservation, and distributed key management. Secure Clustering requires it to detect compromised nodes and remove them from clusters during setup. If compromised nodes bypass the detection mechanism, they may disrupt the clustering process by altering cluster formations or initiating malicious clusters, thereby degrading overall network quality. To address these issues, a new method, Secretary Bird with Self-Organizing Maps (SBWSOM), has been designed to detect and eliminate malicious nodes while efficiently providing data. First, sensor nodes were deployed in a Python-based simulation environment. Second, malicious nodes were identified and eliminated, and the Cluster Head (CH) was selected based on parameters such as residual energy, distance to the base station (BS), and network topology. Furthermore, the data rates of the selected CHs were monitored, and data was transmitted to the sink node. Finally, performance metrics including latency, throughput, packet delivery ratio (PDR), energy consumption, and transmission loss were evaluated. The evaluation of this proposal demonstrated improved data transfer, with a throughput of 0.91, an energy consumption of 0.46 mJ, and a packet delivery ratio of 96.3%. Additionally, the transmission loss was 4.20%, and the latency was 6.04 ms. Overall, this method performed well, with significant improvement over previous models.