Unmasking the Botnet Attacks: A Hybrid Deep Learning Approach

As IoT devices become more integrated, potential risks and vulnerabilities increase. To protect IoT networks, robust security measures are needed. However, current security lacks extensive architecture, making valuable data vulnerable to botnet attacks. Deep learning algorithms can improve botnet detection precision and effectiveness. This hybrid approach strengthens network security by analyzing network traffic patterns and identifying suspicious activity related to botnet operations. This hybrid strategy provides a strong defense against botnet attacks, strengthens network security, and safeguards sensitive data. LSTM-GRU delivers the best outcome for all minority and majority classes, with an average of 0.99 in precision, recall, and F1-score. The study shows how deep learning algorithms can be used effectively to detect botnet activity.