- author = "Gianluigi Folino and Francesco Sergio Pisani",
- title = "Combining Ensemble of Classifiers by using Genetic Programming for Cyber Security Applications",
- booktitle = "18th European Conference on the Applications of Evolutionary Computation",
- year = "2015",
- editor = "Antonio M. Mora and Giovanni Squillero",
- series = "LNCS",
- volume = "9028",
- publisher = "Springer",
- pages = "54--66",
- address = "Copenhagen",
- month = "8-10 " # apr,
- organisation = "EvoStar",
- keywords = "genetic algorithms, genetic programming",
- isbn13 = "978-3-319-16548-6",
-
DOI = "
doi:10.1007/978-3-319-16549-3_5",
-
abstract = "Classification is a relevant task in the cyber
security domain, but it must be able to cope with
unbalanced and/or incomplete datasets and must also
react in real-time to changes in the data. Ensemble of
classifiers are a useful tool for classification in
hard domains as they combine different classifiers that
together provide complementary information. However,
most of the ensemble-based algorithms require an
extensive training phase and need to be re-trained in
case of changes in the data.
This work proposes a Genetic Programming-based framework to generate a function for combining an ensemble, having some interesting properties: the models composing the ensemble are trained only on a portion of the training set, and then, they can be combined and used without any extra phase of training; furthermore, in case of changes in the data, the function can be recomputed in an incrementally way, with a moderate computational effort.
Experiments conducted on unbalanced datasets and on a well-known cyber-security dataset assess the goodness of the approach.",
- notes = "evoCOMNET EvoApplications2015 held in conjunction with EuroGP'2015, EvoCOP2015 and EvoMusArt2015 http://www.evostar.org/2015/cfp_evoapps.php",
