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.

Bibliografiska uppgifter
Huvudupphovsmän: Rahman, Tahsinur, Ahmed, Nusaiba, Monjur, Shama, Haque, Fasbeer Mohammad, Kabir, Naweed
Övriga upphovsmän: Hossain, Dr. Muhammad Iqbal
Materialtyp: Lärdomsprov
Språk:English
Publicerad: Brac University 2023
Ämnen:
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.
Länkar:http://hdl.handle.net/10361/19354

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