Anomaly Intrusion Detection Based on PCA

Document Type : Original Article

Authors

1 Dept. of Electronics and Electrical Communications, Faculty of Electronic Engineering, Minufiya University.

2 Department of Computer Science and Engineering, Faculty of Electronic Engineering, Menoufia

Abstract

This paper proposes an anomaly intrusion detection approach
based on the Principal Component Analysis (PCA) model and
selecting different numbers of effective features, from the
dataset in the presence of several types of attacks. Several
attacks have been considered such as Denial of Service (DoS),
Probing (Prob), Remote to Local (R2L), and User to Root
(U2R) attack. Simulation results conclude that more accuracy
of detection and less false alarms are obtained, in spite of
reducing the number of selected features, and subsequently
reducing complexity.


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