PDFGuardian: An innovative approach to interpretable PDF malware detection using XAI with SHAP framework

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.

Библиографические подробности
Главные авторы:	Rahman, Tahsinur, Ahmed, Nusaiba, Monjur, Shama, Haque, Fasbeer Mohammad, Kabir, Naweed
Другие авторы:	Hossain, Dr. Muhammad Iqbal
Формат:	Диссертация
Язык:	English
Опубликовано:	Brac University 2023
Предметы:	Malware PDF PDF-analysis Cybersecurity SGD Machine-learning Detection Deep learning Artificial neural network Algorithm Single layer perceptron Extreme gradient boosting Explainable artificial intelligence Shapley additive explanations ANN SHAP XAI XGBoost Classifiers Artificial intelligence. Computer security.
Online-ссылка:	http://hdl.handle.net/10361/19354

http://hdl.handle.net/10361/19354

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