Improving Network Intrusion Detection by Means of Domain-Aware Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @InProceedings{Blasco:2010:ARES,
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author = "Jorge Blasco and Agustin Orfila and Arturo Ribagorda",
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title = "Improving Network Intrusion Detection by Means of
Domain-Aware Genetic Programming",
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booktitle = "International Conference on Availability, Reliability,
and Security, ARES '10",
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year = "2010",
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month = feb,
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pages = "327--332",
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abstract = "One of the central areas in network intrusion
detection is how to build effective systems that are
able to distinguish normal from intrusive traffic. In
this paper we explore the use of Genetic Programming
(GP) for such a purpose. Although GP has already been
studied for this task, the inner features of network
intrusion detection have been systematically ignored.
To avoid the blind use of GP shown in previous
research, we guide the search by means of a fitness
function based on recent advances on IDS evaluation.
For the experimental work we use a well-known dataset
(i.e. KDD-99) that has become a standard to compare
research although its drawbacks. Results clearly show
that an intelligent use of GP achieves systems that are
comparable (and even better in realistic conditions) to
top state-of-the-art proposals in terms of
effectiveness, improving them in efficiency and
simplicity.",
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keywords = "genetic algorithms, genetic programming, domain-aware
genetic programming, fitness function, intrusive
traffic, network intrusion detection, normal traffic,
security of data",
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DOI = "doi:10.1109/ARES.2010.53",
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notes = "Also known as \cite{5438073}",
- }
Genetic Programming entries for
Jorge Blasco Alis
Agustin Orfila Diaz-Pabon
D Arturo Ribagorda Garnacho
Citations