Phishing Websites Detection by Using Optimized Stacking Ensemble Model

Phishing attacks are security that do not affect only individuals’ or organizations’ websites but may Internet of Things (IoT) devices and networks. IoT environment is an exposed for such attacks. Attackers use thingbots software the dispersal hidden junk emails noticed by users. Machine deep learning other methods were used to design detection these However, there still a need enhance accuracy. Optimization ensemble classification method phishing website (PW) proposed in this study. A Genetic Algorithm (GA) was optimization tuning several Learning (ML) parameters, including Random Forest (RF), AdaBoost (AB), XGBoost (XGB), Bagging (BA), GradientBoost (GB), LightGBM (LGBM). These accomplished ranking optimized classifiers pick out best as base method. PW dataset made up 4898 PWs 6157 legitimate (LWs) study's experiments. As result, accuracy enhanced reached 97.16 percent.