MISUSE DETECTION - A Neural Network vs. A Genetic Algorithm Approach

Pedro A. Diaz-Gomez; Dean F. Hougen

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Paper

MISUSE DETECTION - A Neural Network vs. A Genetic Algorithm Approach

Topics: Evolutionary Programming

In Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 1: ICEIS, 459-462, 2007 , Funchal, Madeira, Portugal

Authors: Pedro A. Diaz-Gomez and Dean F. Hougen

Affiliation: Robotics, Evolution, Adaptation, and Learning Laboratory (REAL Lab), School of Computer Science, University of Oklahoma, United States

Keyword(s): Misuse detection, genetic algorithms, neural networks, false negative, false positive.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence and Decision Support Systems ; Enterprise Information Systems ; Evolutionary Programming

Abstract: Misuse detection can be addressed as an optimization problem, where the problem is to find an array of possible intrusions x that maximizes a function f (·) subject to a constraint r imposed by a user’s actions performed on a computer. This position paper presents and compares two ways of finding x, in audit data, by using neural networks and genetic algorithms.

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Paper citation in several formats:

A. Diaz-Gomez, P. and F. Hougen, D. (2007). MISUSE DETECTION - A Neural Network vs. A Genetic Algorithm Approach. In Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-972-8865-89-4; ISSN 2184-4992, SciTePress, pages 459-462. DOI: 10.5220/0002410904590462

@conference{iceis07,
author={Pedro {A. Diaz{-}Gomez}. and Dean {F. Hougen}.},
title={MISUSE DETECTION - A Neural Network vs. A Genetic Algorithm Approach},
booktitle={Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2007},
pages={459-462},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002410904590462},
isbn={978-972-8865-89-4},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - MISUSE DETECTION - A Neural Network vs. A Genetic Algorithm Approach
SN - 978-972-8865-89-4
IS - 2184-4992
AU - A. Diaz-Gomez, P.
AU - F. Hougen, D.
PY - 2007
SP - 459
EP - 462
DO - 10.5220/0002410904590462
PB - SciTePress