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

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.

Detalhes bibliográficos
Principais autores: Rahman, Tahsinur, Ahmed, Nusaiba, Monjur, Shama, Haque, Fasbeer Mohammad, Kabir, Naweed
Outros Autores: Hossain, Dr. Muhammad Iqbal
Formato: Tese
Idioma:English
Publicado em: Brac University 2023
Assuntos:
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.
Acesso em linha:http://hdl.handle.net/10361/19354

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