Parallel Model to Detect Attacks Using Evolutionary Based Technique
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- @InProceedings{Guruprasad:2023:ACCESS,
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author = "Sunitha Guruprasad and Rio D'Souza {G. L.}",
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booktitle = "2023 3rd International Conference on Advances in
Computing, Communication, Embedded and Secure Systems
(ACCESS)",
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title = "Parallel Model to Detect Attacks Using Evolutionary
Based Technique",
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year = "2023",
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pages = "291--296",
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abstract = "Evolutionary-based algorithms emerged due to their
flexibility and effectiveness in solving different
varieties of problems. Optimisation-based techniques
are used in finding solutions that involve multiple
conflicting objectives. Parallel evolutionary-based
algorithms are used to overcome the time-consuming job
of finding solutions to these types of problems. In
this paper, we present a parallel genetic
programming-based model that runs parallelly and
obtains solutions in a minimal amount of time. The
model also allows the user to select the best set of
objectives based on the requirements of the users. An
island model is used which runs the operations on
different islands parallelly. This not only decreases
the execution time of the process but also increases
the diversity of the population. The results obtained
in different islands are fed to an ensemble classifier
to get the required result. The model was trained and
tested using the state-of-the-art ISCX-2012 and
CICIDS2017 datasets. In our work, we have mainly
focused on detecting the attacks in a system in a short
duration of time. The model developed gave significant
performance improvement compared to the results
obtained using the normal CPU implementation.",
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keywords = "genetic algorithms, genetic programming, Computational
modelling, Sociology, Genetics, Main-secondary,
Statistics, Testing, Ensemble, Evolutionary, Parallel,
Island model, Optimisation",
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DOI = "doi:10.1109/ACCESS57397.2023.10200912",
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month = may,
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notes = "Also known as \cite{10200912}",
- }
Genetic Programming entries for
Sunitha Gp
Rio D'Souza G L
Citations