MalFam: a comprehensive study on malware families with state-of-the-art CNN architectures with classifications and XAI

MalFam: a comprehensive study on malware families with state-of-the-art CNN architectures with classifications and XAI

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.

Detalhes bibliográficos
Principais autores: Haque, Abid Hossain, Jahin, Labiba Ifrit, Katib, Sheikh Yasir Hossain, Tuhee, Saiwara Mahmud, Tasnia, Maisoon
Outros Autores: Hossain, Muhammad Iqbal
Formato: Tese
Idioma:English
Publicado em: Brac University 2024
Assuntos:
Explainable artificial intelligence (XAI)
Convolutional neural network (CNN)
DenseNet
Inception ResNet V2
VGG16
Comparative analysis
Neural networks (Computer science)
Artificial intelligence
Acesso em linha:http://hdl.handle.net/10361/22824

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