srjecsSRJECSSRJECS2788-9408https://doi.org/10.47310/srjms.2025.v05i02.001Deep Learning-Based Intrusion Detection in Wireless Sensor Networks using Optimized Convolutional Neural Network with IGOA AlgorithmIntisarKhalaf SalehTechnical Engineering College Kirkuk, Northern Technical University, IraqThe open nature and resource limitations of Wireless Sensor Networks (WSNs) make them more exposed to numerous cyber threats. IDSs function effectively as key components for securing such networks. The research introduces a new deep learning intrusion detection system that integrates IGOA with CNN to enhance WSN intrusion detection capabilities. IGOA automatically optimizes CNN classification performance through an improvement of both accuracy and generalization capabilities. The proposed method demonstrates superior performance in WSN-DS dataset experiments since it reaches 99.94% accuracy that exceeds several state-of-the-art methods. Multiple assessments of precision, recall, F1-score and confusion matrix analysis and ROC-AUC metrics prove that the model can deliver reliable performance in real-world applications.