A cost sensitive learning algorithm for intrusion detection

In this paper, a novel cost-sensitive learning algorithm is proposed to improve the performance of the nearest neighbor rule for intrusion detection. The goal of the learning algorithm is to minimize the total cost of misclassifications in leave-one-out test. This is important since in intrusion det...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Ghodratnama, S, Moosavi, M R, Taheri, M, Zolghadri Jahromi, M
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Adaptive distance measure Classification algorithms component Computer science Cost function Data security Feature weighting Instance weighting Intrusion detection KDD99 Nearest neighbor Nearest neighbor searches Neural networks System testing Training data Weight measurement
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!