Improving malware detection with neuroevolution : a study with the semantic learning machine

Detalhes bibliográficos
Autor(a) principal: Teixeira, Mário José Santos
Data de Publicação: 2019
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/79565
Resumo: Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence
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spelling Improving malware detection with neuroevolution : a study with the semantic learning machineGeometric semantic genetic programmingArtificial Neural NetworksGenetic ProgrammingSupervised LearningSemantic Learning MachineMultilayer Neural NetworksProject Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceMachine learning has become more attractive over the years due to its remarkable adaptation and problem-solving abilities. Algorithms compete amongst each other to claim the best possible results for every problem, being one of the most valued characteristics their generalization ability. A recently proposed methodology of Genetic Programming (GP), called Geometric Semantic Genetic Programming (GSGP), has seen its popularity rise over the last few years, achieving great results compared to other state-of-the-art algorithms, due to its remarkable feature of inducing a fitness landscape with no local optima solutions. To any supervised learning problem, where a metric is used as an error function, GSGP’s landscape will be unimodal, therefore allowing for genetic algorithms to behave much more efficiently and effectively. Inspired by GSGP’s features, Gonçalves developed a new mutation operator to be applied to the Neural Networks (NN) domain, creating the Semantic Learning Machine (SLM). Despite GSGP’s good results already proven, there are still research opportunities for improvement, that need to be performed to empirically prove GSGP as a state-of-the-art framework. In this case, the study focused on applying SLM to NNs with multiple hidden layers and compare its outputs to a very popular algorithm, Multilayer Perceptron (MLP), on a considerably large classification dataset about Android malware. Findings proved that SLM, sharing common parametrization with MLP, in order to have a fair comparison, is able to outperform it, with statistical significance.Gonçalves, Ivo Carlos PereiraCastelli, MauroRUNTeixeira, Mário José Santos2019-08-29T15:46:27Z2019-07-012019-07-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/79565TID:202278174enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T04:35:18Zoai:run.unl.pt:10362/79565Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:35:48.764031Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Improving malware detection with neuroevolution : a study with the semantic learning machine
title Improving malware detection with neuroevolution : a study with the semantic learning machine
spellingShingle Improving malware detection with neuroevolution : a study with the semantic learning machine
Teixeira, Mário José Santos
Geometric semantic genetic programming
Artificial Neural Networks
Genetic Programming
Supervised Learning
Semantic Learning Machine
Multilayer Neural Networks
title_short Improving malware detection with neuroevolution : a study with the semantic learning machine
title_full Improving malware detection with neuroevolution : a study with the semantic learning machine
title_fullStr Improving malware detection with neuroevolution : a study with the semantic learning machine
title_full_unstemmed Improving malware detection with neuroevolution : a study with the semantic learning machine
title_sort Improving malware detection with neuroevolution : a study with the semantic learning machine
author Teixeira, Mário José Santos
author_facet Teixeira, Mário José Santos
author_role author
dc.contributor.none.fl_str_mv Gonçalves, Ivo Carlos Pereira
Castelli, Mauro
RUN
dc.contributor.author.fl_str_mv Teixeira, Mário José Santos
dc.subject.por.fl_str_mv Geometric semantic genetic programming
Artificial Neural Networks
Genetic Programming
Supervised Learning
Semantic Learning Machine
Multilayer Neural Networks
topic Geometric semantic genetic programming
Artificial Neural Networks
Genetic Programming
Supervised Learning
Semantic Learning Machine
Multilayer Neural Networks
description Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence
publishDate 2019
dc.date.none.fl_str_mv 2019-08-29T15:46:27Z
2019-07-01
2019-07-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/79565
TID:202278174
url http://hdl.handle.net/10362/79565
identifier_str_mv TID:202278174
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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