Enhancing intrusion detection systems: Innovative deep learning approaches using CNN, RNN, DBN and autoencoders for robust network security
The increasing sophistication of cyber threats poses significant challenges to network security.This makes effective intrusion detection system (IDS) more important than ever before.Conventional IDS methods, which often rely on signatures or rules it will struggle to Cape keep up with its complex attacks and evolution.This thesis evaluates and anal