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.

Bibliografiska uppgifter
Huvudupphovsmän: Haque, Abid Hossain, Jahin, Labiba Ifrit, Katib, Sheikh Yasir Hossain, Tuhee, Saiwara Mahmud, Tasnia, Maisoon
Övriga upphovsmän: Hossain, Muhammad Iqbal
Materialtyp: Lärdomsprov
Språk:English
Publicerad: Brac University 2024
Ämnen:
Explainable artificial intelligence (XAI)
Convolutional neural network (CNN)
DenseNet
Inception ResNet V2
VGG16
Comparative analysis
Neural networks (Computer science)
Artificial intelligence
Länkar:http://hdl.handle.net/10361/22824

Internet

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

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