Md. Tamim Hasan Saykat

An efficient and interpretable intrusion detection framework for software-defined networks with multi-class imbalanced data using genetic and GAN-based optimization

A hybrid SDN-based IDS framework that integrates Generative Adversarial Networks (GANs) to handle imbalanced datasets, one-way ANOVA and Genetic Algorithm for feature selection, baseline classifier optimization using Grid Search and Explainable AI techniques to achieve robust, accurate, and interpretable intrusion detection.