University Sétif 1 FERHAT ABBAS Faculty of Sciences
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Auteur Mehdi Benzine |
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Titre : Detecting SQL injections using Deep Learning techniques Type de document : texte imprimé Auteurs : Rami Athmani, Auteur ; Nassim Bouhezila, Auteur ; Mehdi Benzine, Directeur de thèse Année de publication : 2023 Importance : 1 vol (77 f .) Format : 29cm Langues : Français (fre) Catégories : Thèses & Mémoires:Informatique Mots-clés : Deep learning
Deep learning techniquesIndex. décimale : 004 Informatique Résumé : Deep learning techniques have improved various domains by using their ability to learn complex patterns from large datasets. In this dissertation, we employed the power of Deep Learning, specifically BERT language model (Bidirectional Encoder Representations from Transformers), to resolve the issue of SQL injection attacks on web applications. The goal of our study is to develop a Deep Learning model using BERT that can accurately identify SQL injections. Based on the results, our model demonstrated excellent performance; it also indicated that BERT outperforms the compared machine learning models across different evaluation metrics. These results affirm the effectiveness of BERT in detecting SQL injection attacks, underscoring its superior performance in our study. Côte titre : MAI/0703 En ligne : https://drive.google.com/file/d/1Y4x5rP9fBhMfyFO3X6jTI4qEX1jXvZjZ/view?usp=drive [...] Format de la ressource électronique : Detecting SQL injections using Deep Learning techniques [texte imprimé] / Rami Athmani, Auteur ; Nassim Bouhezila, Auteur ; Mehdi Benzine, Directeur de thèse . - 2023 . - 1 vol (77 f .) ; 29cm.
Langues : Français (fre)
Catégories : Thèses & Mémoires:Informatique Mots-clés : Deep learning
Deep learning techniquesIndex. décimale : 004 Informatique Résumé : Deep learning techniques have improved various domains by using their ability to learn complex patterns from large datasets. In this dissertation, we employed the power of Deep Learning, specifically BERT language model (Bidirectional Encoder Representations from Transformers), to resolve the issue of SQL injection attacks on web applications. The goal of our study is to develop a Deep Learning model using BERT that can accurately identify SQL injections. Based on the results, our model demonstrated excellent performance; it also indicated that BERT outperforms the compared machine learning models across different evaluation metrics. These results affirm the effectiveness of BERT in detecting SQL injection attacks, underscoring its superior performance in our study. Côte titre : MAI/0703 En ligne : https://drive.google.com/file/d/1Y4x5rP9fBhMfyFO3X6jTI4qEX1jXvZjZ/view?usp=drive [...] Format de la ressource électronique : Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité MAI/0703 MAI/0703 Mémoire Bibliothéque des sciences Anglais Disponible
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