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A Review on Network Intrusion Detection using Machine Learning: Feature Selection Approach
Author Name : Ruchi Mulay, Gargi Shankar Verma
ABSTRACT
An intrusion detection system (IDS) intention to differentiate between intrusion activity and normal actions. In doing so, conversely, an IDS can familiarize classification errors. A false positive is a gentle input for which the system speciously raises a notification. A false negative, in contrast, is a malevolent input that the IDS miscarries to report. The appropriately classified input data are typically mentioned to as true positives (suspicious attacks) and true negatives (normal traffic). In this paper we have reviewed different machine learning approach for IDS, concluded that feature selection is essential to enhance the prediction accuracy, also reviewed meta heuristic approach for feature selection.
Keywords— ID, NIDS, GWO,PSO, KDD, ML, DM