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.

Bibliographische Detailangaben
Hauptverfasser: Haque, Abid Hossain, Jahin, Labiba Ifrit, Katib, Sheikh Yasir Hossain, Tuhee, Saiwara Mahmud, Tasnia, Maisoon
Weitere Verfasser: Hossain, Muhammad Iqbal
Format: Abschlussarbeit
Sprache:English
Veröffentlicht: Brac University 2024
Schlagworte:
Explainable artificial intelligence (XAI)
Convolutional neural network (CNN)
DenseNet
Inception ResNet V2
VGG16
Comparative analysis
Neural networks (Computer science)
Artificial intelligence
Online Zugang:http://hdl.handle.net/10361/22824

Online

http://hdl.handle.net/10361/22824

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