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.

Opis bibliograficzny
Główni autorzy: Rahman, Tahsinur, Ahmed, Nusaiba, Monjur, Shama, Haque, Fasbeer Mohammad, Kabir, Naweed
Kolejni autorzy: Hossain, Dr. Muhammad Iqbal
Format: Praca dyplomowa
Język:English
Wydane: Brac University 2023
Hasła przedmiotowe:
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.
Dostęp online:http://hdl.handle.net/10361/19354

Internet

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

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