University Sétif 1 FERHAT ABBAS Faculty of Sciences
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Titre : http flood dos attack detection using data mining Type de document : texte imprimé Auteurs : yasmina Abidi, Auteur ; yaakoub Derradji, Auteur ; Haddadi ,Mohamed, Directeur de thèse Année de publication : 2022 Importance : 1 vol (94 f .) Format : 29cm Langues : Français (fre) Catégories : Thèses & Mémoires:Informatique Mots-clés : Informatique Index. décimale : 004 Informatique Résumé :
Among the problems that the Internet is facing now is DOS ATTACKS. It aims
to deny services to legitimate users, and shut down a machine or network, making
it inaccessible to its intended users. It will be through flooding the target with
requests or sending information that triggers a crash. There are many types of DoS
attacks, including Slowloris Attack, RUDY Attack, Slow HTTP Post Attack, and
Slow Read Attack. To detect this attack we use Data Mining, and the two tools
WEKKA and TANAGRA. Data mining is the process to extract information from
a dataset to help to make a decision. In our case, the decision is to classify requests
as normal or abnormal (attack). To reach this goal; we used a classification
algorithm, we chose among them Multilayer Perceptron, Naive Bayes, Random
Tree, K-Nearest Neighbors, Decision Tree, and Support Vector Machine. We
have implemented these algorithms on http_csic_2010_full.arff dataset. We are
looking for a program that gives a high rate and the perfect classification of attacks.Côte titre : MAI/0583 En ligne : https://drive.google.com/file/d/1s-MQJt1dRtsvA15TT5YIKcO_g0Ki1TFq/view?usp=share [...] Format de la ressource électronique : http flood dos attack detection using data mining [texte imprimé] / yasmina Abidi, Auteur ; yaakoub Derradji, Auteur ; Haddadi ,Mohamed, Directeur de thèse . - 2022 . - 1 vol (94 f .) ; 29cm.
Langues : Français (fre)
Catégories : Thèses & Mémoires:Informatique Mots-clés : Informatique Index. décimale : 004 Informatique Résumé :
Among the problems that the Internet is facing now is DOS ATTACKS. It aims
to deny services to legitimate users, and shut down a machine or network, making
it inaccessible to its intended users. It will be through flooding the target with
requests or sending information that triggers a crash. There are many types of DoS
attacks, including Slowloris Attack, RUDY Attack, Slow HTTP Post Attack, and
Slow Read Attack. To detect this attack we use Data Mining, and the two tools
WEKKA and TANAGRA. Data mining is the process to extract information from
a dataset to help to make a decision. In our case, the decision is to classify requests
as normal or abnormal (attack). To reach this goal; we used a classification
algorithm, we chose among them Multilayer Perceptron, Naive Bayes, Random
Tree, K-Nearest Neighbors, Decision Tree, and Support Vector Machine. We
have implemented these algorithms on http_csic_2010_full.arff dataset. We are
looking for a program that gives a high rate and the perfect classification of attacks.Côte titre : MAI/0583 En ligne : https://drive.google.com/file/d/1s-MQJt1dRtsvA15TT5YIKcO_g0Ki1TFq/view?usp=share [...] Format de la ressource électronique : Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité MAI/0583 MAI/0583 Mémoire Bibliothéque des sciences Anglais Disponible
Disponible