A Distributed Intrusion Detection Framework Based on Evolved Specialized Ensembles of Classifiers
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- @InProceedings{Folino:2016:EvoApps,
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author = "Gianluigi Folino and Francesco Sergio Pisani and
Pietro Sabatino",
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title = "A Distributed Intrusion Detection Framework Based on
Evolved Specialized Ensembles of Classifiers",
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booktitle = "EvoApplications 2016",
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year = "2016",
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editor = "Giovanni Squillero and Paolo Burelli",
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volume = "9597",
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series = "LNCS",
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pages = "315--331",
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address = "Porto, Portugal",
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month = mar # " 30-" # apr # " 1",
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organisation = "Species",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-3-319-31204-0",
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DOI = "doi:10.1007/978-3-319-31204-0_21",
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abstract = "Modern intrusion detection systems must handle many
complicated issues in real-time, as they have to cope
with a real data stream; indeed, for the task of
classification, typically the classes are unbalanced
and, in addition, they have to cope with distributed
attacks and they have to quickly react to changes in
the data. Data mining techniques and, in particular,
ensemble of classifiers permit to combine different
classifiers that together provide complementary
information and can be built in an incremental way.
This paper introduces the architecture of a distributed
intrusion detection framework and in particular, the
detector module based on a meta-ensemble, which is used
to cope with the problem of detecting intrusions, in
which typically the number of attacks is minor than the
number of normal connections. To this aim, we explore
the usage of ensembles specialized to detect particular
types of attack or normal connections, and Genetic
Programming is adopted to generate a non-tra",
- }
Genetic Programming entries for
Gianluigi Folino
Francesco Sergio Pisani
Pietro Sabatino
Citations