An enhanced classification framework for intrusions detection system using intelligent exoplanet atmospheric retrieval algorithm

Currently, many companies use data mining for various implementations. One form of implementation is intrusion detection system (IDS). In IDS, the main problem nuisance network administrators in detecting attacks false alerts. Regardless methods implemented by this system, eliminating alerts still a huge problem. To describe traffic passing through network, database security layer (NSL) knowledge discovery (KDD) dataset used. The massive sent over contains excessive and duplicated amounts information. This causes classifier to be biased, reduce classification accuracy, increase alert. that end, we proposed model significantly improve accuracy alerts, whether they are negative or positive results show intelligent exoplanet atmospheric retrieval (INARA) algorithm has improved able detect new attack types efficiently.