Gesellschaft fr Informatik e.V.

Lecture Notes in Informatics


SICHERHEIT 2005, Sicherheit - Schutz und Zuverlässigkeit, Beiträge der 2. Jahrestagung des Fachbereichs Sicherheit der Gesellschaft für Informatik e.V. (GI), 5.-8. April 2005 in Regensburg. GI 2005 P-62, 197-208 (2005).

GI, Gesellschaft für Informatik, Bonn
2005


Editors

Hannes Federrath (ed.)


Copyright © GI, Gesellschaft für Informatik, Bonn

Contents

Visualization of anomaly detection using prediction sensitivity

P. Laskov , K. Rieck , C. Schäfer and K. -R. Müller

Abstract


Visualization of learning-based intrusion detection methods is a challenging problem. In this paper we propose a novel method for visualization of anomaly detection and feature selection, based on prediction sensitivity. The method allows an expert to discover informative features for separation of normal and attack instances. Experiments performed on the KDD Cup dataset show that explanations provided by prediction sensitivity reveal the nature of attacks. Application of prediction sensitivity for feature selection yields a major improvement of detection accuracy.


Full Text: PDF

GI, Gesellschaft für Informatik, Bonn
ISBN 3-88579-391-1


Last changed 24.01.2012 21:48:55