Intrusion Insight-Forecasting Cyber Attacks using Network Intrusion Detection Systems

This study examines how improving the predic- tion of cyberattacks can be achieved by combining predictive modelling with Network Intrusion Detection Systems (NIDS). Proactive detection is essential for efficient cyber security as cyber threats change. We offer a system for analysing real-time network behaviour from NIDS and historical attack data using machine learning. Our method increases accuracy and reaction times by emphasising feature selection, data preprocessing, and different predictive models. According to experimental findings, this in- tegrated approach performs noticeably better than conventional detection methods and offers early warnings of possible hazards. With the help of this framework, organisations can improve situational awareness and lessen the effects of cyberattacks.