INTRUSION DETECTION SYSTEM WITH FEATURE SELECTION APPROACH TO REDUCE CYBER ANOMALY RATE

The present paper offers an extensive analysis of search engine accessibility, stressing its advantages, disadvantages, and evolution over time. It assesses the many alternatives available in IDS and shows how well they work to lessen computational load while raising suspicion accuracy. This article also outlines the decision to incorporate statistical, data mining, and machine learning techniques into the IDS framework's characteristics. It assesses how well these procedures reduce vulnerabilities, increase detection rates, and adjust to evolving cyber threats.