Détection d’intrusions informatiques via le deep learning

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dc.contributor.authorMadouni, Riad
dc.contributor.authorHadj Said, Houcine Zakaria
dc.contributor.authorBelgrana, Fatima Zohra
dc.date.accessioned2024-12-10T14:04:09Z
dc.date.available2024-12-10T14:04:09Z
dc.date.issued2023
dc.identifier.urihttp://dspace.univ-temouchent.edu.dz/handle/123456789/5860
dc.language.isofren_US
dc.subjectIntrusionDetectionSystem(IDS),deeplearning,visiontransformers,featureselection, variancerate,randomforests,dimensionalityreduction,randomsampling,NSLKDD,CIC2017en_US
dc.subjectSystèmededétectiond’intrusion(SDI),apprentissageprofond,transformateursde vision, sélectiondescaractéristiques,tauxdevariance,forêtsaléatoires,réductiondedimensionnalité, échantillonnagealéatoire,NSLKDD,CIC2017.en_US
dc.titleDétection d’intrusions informatiques via le deep learningen_US
dc.typeThesisen_US

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