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.

Podrobná bibliografie
Hlavní autoři:	Rahman, Tahsinur, Ahmed, Nusaiba, Monjur, Shama, Haque, Fasbeer Mohammad, Kabir, Naweed
Další autoři:	Hossain, Dr. Muhammad Iqbal
Médium:	Diplomová práce
Jazyk:	English
Vydáno:	Brac University 2023
Témata:	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.
On-line přístup:	http://hdl.handle.net/10361/19354

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

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