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Computers & Security
Volume 13, Issue 6, 1994, Pages 495-508
 
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doi:10.1016/0167-4048(91)90138-4    How to Cite or Link Using DOI (Opens New Window)
Copyright © 1994 Published by Elsevier Science Ltd. All rights reserved.

Refereed paper

Intrusion detection: Approach and performance issues of the SECURENET system*1

Michel Denault and Dimitris Karagiannis

Dimitris Gritzalis

Paul Spirakis

Institute for Applied Computer Science and Information Systems, Department of Knowledge Engineering, University of Vienna, Bruenner Str. 72, Wien A-1210, Austria Department of Informatics, Technological Educational Institute (TEI) of Athens, Egaleo GR-12210, Athens, Greece Department of Mathematics, University of the Aegean, Samos GR-83200, Aegean, Greece Department of Computer Engineering and Informatics, University of Patras, Rio, Patras GR-26000, Greece

Available online 15 April 2002.

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Abstract

The first aim of this paper is to provide a comparison between the generic characteristics of the detection-by-appearance and the detection-by-behaviour models for malicious software intrusion detection, and thus to discuss the efficiency of intrusion detection systems based on AI technologies. We introduce the SECURENET system, an experimental intrusion detection intelligent system, which incorporates the use of expert systems, neural networks, and intent specification languages. The second goal is to present the basis of a reaction- time delay analysis for SECURENET in a typical WAN environment. Together with the proportion of attacks detected, reaction time is one of the main efficiency criteria of an intrusion detection system.

Author Keywords: Intrusion detection; Malicious software; SECURENET system; Intent specification languages; Expert systems; Neural networks

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